Subjects -> BUSINESS AND ECONOMICS (Total: 3841 journals)
    - ACCOUNTING (145 journals)
    - BANKING AND FINANCE (329 journals)
    - BUSINESS AND ECONOMICS (1411 journals)
    - CONSUMER EDUCATION AND PROTECTION (20 journals)
    - COOPERATIVES (4 journals)
    - ECONOMIC SCIENCES: GENERAL (232 journals)
    - ECONOMIC SYSTEMS, THEORIES AND HISTORY (255 journals)
    - FASHION AND CONSUMER TRENDS (20 journals)
    - HUMAN RESOURCES (103 journals)
    - INSURANCE (26 journals)
    - INTERNATIONAL COMMERCE (146 journals)
    - INTERNATIONAL DEVELOPMENT AND AID (103 journals)
    - INVESTMENTS (22 journals)
    - LABOR AND INDUSTRIAL RELATIONS (66 journals)
    - MACROECONOMICS (17 journals)
    - MANAGEMENT (634 journals)
    - MARKETING AND PURCHASING (116 journals)
    - MICROECONOMICS (23 journals)
    - PRODUCTION OF GOODS AND SERVICES (125 journals)
    - PUBLIC FINANCE, TAXATION (42 journals)
    - TRADE AND INDUSTRIAL DIRECTORIES (2 journals)

BUSINESS AND ECONOMICS (1411 journals)                  1 2 3 4 5 6 7 8 | Last

Showing 1 - 200 of 1566 Journals sorted alphabetically
360 : Revista de Ciencias de la Gestión     Open Access   (Followers: 14)
4OR: A Quarterly Journal of Operations Research     Hybrid Journal   (Followers: 14)
Abacus     Hybrid Journal   (Followers: 21)
Accounting Forum     Hybrid Journal   (Followers: 33)
Acta Amazonica     Open Access   (Followers: 7)
Acta Commercii     Open Access   (Followers: 5)
Acta Marisiensis : Seria Oeconomica     Open Access   (Followers: 1)
Acta Oeconomica     Full-text available via subscription   (Followers: 4)
Acta Scientiarum. Human and Social Sciences     Open Access   (Followers: 11)
Acta Universitatis Danubius. Œconomica     Open Access   (Followers: 4)
Acta Universitatis Lodziensis : Folia Geographica Socio-Oeconomica     Open Access   (Followers: 2)
Acta Universitatis Nicolai Copernici Zarządzanie     Open Access   (Followers: 5)
AD-minister     Open Access   (Followers: 5)
Adam Academy : Journal of Social Sciences / Adam Akademi : Sosyal Bilimler Dergisi     Open Access   (Followers: 6)
AdBispreneur : Jurnal Pemikiran dan Penelitian Administrasi Bisnis dan Kewirausahaan     Open Access   (Followers: 1)
Admisi dan Bisnis     Open Access   (Followers: 1)
ADR Bulletin     Open Access   (Followers: 10)
Advanced Sustainable Systems     Hybrid Journal   (Followers: 8)
Advances in Developing Human Resources     Hybrid Journal   (Followers: 35)
Advances in Economics and Business     Open Access   (Followers: 27)
Africa Journal of Management     Hybrid Journal   (Followers: 3)
African Affairs     Hybrid Journal   (Followers: 78)
African Business     Full-text available via subscription   (Followers: 6)
African Development Review     Hybrid Journal   (Followers: 46)
African Journal of Business Ethics     Open Access   (Followers: 8)
African Review of Economics and Finance     Open Access   (Followers: 8)
Afro Eurasian Studies     Open Access   (Followers: 2)
Afro-Asian Journal of Finance and Accounting     Hybrid Journal   (Followers: 9)
Agronomy     Open Access   (Followers: 18)
Akademik Yaklaşımlar Dergisi     Open Access   (Followers: 1)
Akademika : Journal of Southeast Asia Social Sciences and Humanities     Open Access   (Followers: 8)
AL-Qadisiyah Journal For Administrative and Economic sciences     Open Access   (Followers: 3)
Alphanumeric Journal : The Journal of Operations Research, Statistics, Econometrics and Management Information Systems     Open Access   (Followers: 11)
American Economic Journal : Applied Economics     Full-text available via subscription   (Followers: 281)
American Enterprise Institute     Free   (Followers: 3)
American Journal of Business     Hybrid Journal   (Followers: 23)
American Journal of Business and Management     Open Access   (Followers: 73)
American Journal of Business Education     Open Access   (Followers: 17)
American Journal of Economics and Business Administration     Open Access   (Followers: 40)
American Journal of Economics and Sociology     Hybrid Journal   (Followers: 45)
American Journal of Evaluation     Hybrid Journal   (Followers: 18)
American Journal of Finance and Accounting     Hybrid Journal   (Followers: 25)
American Journal of Health Economics     Full-text available via subscription   (Followers: 22)
American Journal of Industrial and Business Management     Open Access   (Followers: 31)
American Journal of Medical Quality     Hybrid Journal   (Followers: 13)
American Law and Economics Review     Hybrid Journal   (Followers: 33)
ANALES de la Universidad Central del Ecuador     Open Access   (Followers: 4)
Ankara University SBF Journal     Open Access   (Followers: 1)
Annales de l'Institut Henri Poincare (C) Non Linear Analysis     Full-text available via subscription   (Followers: 2)
Annals in Social Responsibility     Full-text available via subscription  
Annals of Finance     Hybrid Journal   (Followers: 37)
Annals of Operations Research     Hybrid Journal   (Followers: 12)
Annual Review of Economics     Full-text available via subscription   (Followers: 52)
Anuario Facultad de Ciencias Económicas y Empresariales     Open Access   (Followers: 2)
Applied Developmental Science     Hybrid Journal   (Followers: 4)
Applied Economics     Hybrid Journal   (Followers: 61)
Applied Economics Letters     Hybrid Journal   (Followers: 35)
Applied Financial Economics     Hybrid Journal   (Followers: 29)
Applied Mathematical Finance     Hybrid Journal   (Followers: 9)
Applied Stochastic Models in Business and Industry     Hybrid Journal   (Followers: 7)
Apuntes Universitarios     Open Access   (Followers: 1)
Arab Economic and Business Journal     Open Access   (Followers: 7)
Archives of Business Research     Open Access   (Followers: 12)
Arena Journal     Full-text available via subscription  
Argomenti. Rivista di economia, cultura e ricerca sociale     Open Access   (Followers: 4)
ASEAN Economic Bulletin     Full-text available via subscription   (Followers: 7)
Asia Pacific Business Review     Hybrid Journal   (Followers: 9)
Asia Pacific Journal of Human Resources     Hybrid Journal   (Followers: 331)
Asia Pacific Journal of Innovation and Entrepreneurship     Open Access   (Followers: 3)
Asia Pacific Viewpoint     Hybrid Journal   (Followers: 5)
Asia-Pacific Journal of Business Administration     Hybrid Journal   (Followers: 6)
Asia-Pacific Journal of Operational Research     Hybrid Journal   (Followers: 3)
Asia-Pacific Journal of Rural Development     Hybrid Journal   (Followers: 2)
Asia-Pacific Management and Business Application     Open Access   (Followers: 3)
Asian Business Review     Open Access   (Followers: 5)
Asian Case Research Journal     Hybrid Journal   (Followers: 1)
Asian Development Review     Open Access   (Followers: 16)
Asian Economic Journal     Hybrid Journal   (Followers: 10)
Asian Economic Papers     Hybrid Journal   (Followers: 8)
Asian Economic Policy Review     Hybrid Journal   (Followers: 7)
Asian Journal of Accounting and Governance     Open Access   (Followers: 5)
Asian Journal of Business Ethics     Hybrid Journal   (Followers: 13)
Asian Journal of Economics, Business and Accounting     Open Access   (Followers: 2)
Asian Journal of Social Sciences and Management Studies     Open Access   (Followers: 9)
Asian Journal of Sustainability and Social Responsibility     Open Access   (Followers: 4)
Asian Journal of Technology Innovation     Hybrid Journal   (Followers: 7)
Asian-pacific Economic Literature     Hybrid Journal   (Followers: 9)
AStA Wirtschafts- und Sozialstatistisches Archiv     Hybrid Journal   (Followers: 5)
ATA Journal of Legal Tax Research     Hybrid Journal   (Followers: 7)
Atlantic Economic Journal     Hybrid Journal   (Followers: 13)
Australasian Journal of Regional Studies, The     Full-text available via subscription   (Followers: 1)
Australian Cottongrower, The     Full-text available via subscription   (Followers: 1)
Australian Economic Papers     Hybrid Journal   (Followers: 9)
Australian Economic Review     Hybrid Journal   (Followers: 4)
Australian Journal of Maritime and Ocean Affairs     Hybrid Journal   (Followers: 9)
Balkan Region Conference on Engineering and Business Education     Open Access   (Followers: 2)
Baltic Journal of Real Estate Economics and Construction Management     Open Access   (Followers: 6)
Banks in Insurance Report     Hybrid Journal   (Followers: 1)
BBR - Brazilian Business Review     Open Access   (Followers: 5)
Benchmarking : An International Journal     Hybrid Journal   (Followers: 9)
Benefit : Jurnal Manajemen dan Bisnis     Open Access   (Followers: 1)
Berkeley Business Law Journal     Free   (Followers: 13)
Beta : Scandinavian Journal of Business Research     Full-text available via subscription  
Bio-based and Applied Economics     Open Access   (Followers: 2)
Biodegradation     Hybrid Journal   (Followers: 2)
Biology Direct     Open Access   (Followers: 10)
BizInfo (Blace) Journal of Economics, Management and Informatics     Open Access   (Followers: 1)
Black Enterprise     Full-text available via subscription  
Board & Administrator for Administrators only     Hybrid Journal  
Boletim Técnico do Senac     Open Access  
Border Crossing : Transnational Working Papers     Open Access   (Followers: 3)
Brazilian Business Review     Open Access  
Briefings in Real Estate Finance     Hybrid Journal   (Followers: 7)
British Journal of Industrial Relations     Hybrid Journal   (Followers: 47)
Brookings Papers on Economic Activity     Open Access   (Followers: 72)
Brookings Trade Forum     Full-text available via subscription   (Followers: 4)
BRQ Business Research Quarterly     Open Access   (Followers: 3)
BU Academic Review     Open Access  
Bulletin of Economic Research     Hybrid Journal   (Followers: 20)
Bulletin of Geography. Socio-economic Series     Open Access   (Followers: 4)
Bulletin of Indonesian Economic Studies     Hybrid Journal   (Followers: 4)
Bulletin of the Dnipropetrovsk University. Series : Management of Innovations     Open Access   (Followers: 1)
Business & Entrepreneurship Journal     Open Access   (Followers: 35)
Business & Information Systems Engineering     Hybrid Journal   (Followers: 6)
Business & Society     Hybrid Journal   (Followers: 15)
Business : Theory and Practice / Verslas : Teorija ir Praktika     Open Access   (Followers: 1)
Business and Economic Research     Open Access   (Followers: 13)
Business and Management Horizons     Open Access   (Followers: 15)
Business and Management Research     Open Access   (Followers: 24)
Business and Management Studies     Open Access   (Followers: 20)
Business and Professional Communication Quarterly     Hybrid Journal   (Followers: 9)
Business and Society Review     Hybrid Journal   (Followers: 6)
Business Economics     Hybrid Journal   (Followers: 16)
Business Ethics Quarterly     Full-text available via subscription   (Followers: 20)
Business Ethics: A European Review     Hybrid Journal   (Followers: 21)
Business Horizons     Hybrid Journal   (Followers: 12)
Business Information Review     Hybrid Journal   (Followers: 17)
Business Management Analysis Journal     Open Access   (Followers: 4)
Business Management and Strategy     Open Access   (Followers: 51)
Business Research     Open Access   (Followers: 4)
Business Review Journal     Open Access   (Followers: 1)
Business Strategy and Development     Hybrid Journal   (Followers: 2)
Business Strategy and the Environment     Hybrid Journal   (Followers: 13)
Business Strategy Review     Hybrid Journal   (Followers: 16)
Business Strategy Series     Hybrid Journal   (Followers: 8)
Business Systems & Economics     Open Access   (Followers: 2)
Business, Economics and Management Research Journal : BEMAREJ     Open Access   (Followers: 7)
Business, Management and Education     Open Access   (Followers: 22)
Business: Theory and Practice     Open Access   (Followers: 1)
Cadernos EBAPE.BR     Open Access   (Followers: 1)
Cambridge Journal of Economics     Hybrid Journal   (Followers: 81)
Cambridge Journal of Regions, Economy and Society     Hybrid Journal   (Followers: 13)
Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration     Hybrid Journal   (Followers: 1)
Canadian Journal of Economics/Revue Canadienne d`Economique     Hybrid Journal   (Followers: 44)
Canadian journal of nonprofit and social economy research     Open Access   (Followers: 3)
Capitalism Nature Socialism     Hybrid Journal   (Followers: 27)
Case Studies in Business and Management     Open Access   (Followers: 15)
CBU International Conference Proceedings     Open Access   (Followers: 2)
Central European Business Review     Open Access   (Followers: 2)
Central European Journal of Operations Research     Hybrid Journal   (Followers: 5)
Central European Journal of Public Policy     Open Access   (Followers: 3)
CESifo Economic Studies     Hybrid Journal   (Followers: 24)
Chain Reaction     Full-text available via subscription  
Challenge     Full-text available via subscription   (Followers: 6)
Chandrakasem Rajabhat University Journal of Graduate School     Open Access  
China & World Economy     Hybrid Journal   (Followers: 21)
China : An International Journal     Full-text available via subscription   (Followers: 22)
China Economic Journal : The Official Journal of the China Center for Economic Research (CCER) at Peking University     Hybrid Journal   (Followers: 16)
China Economic Review     Hybrid Journal   (Followers: 16)
China Finance Review International     Hybrid Journal   (Followers: 7)
China perspectives     Open Access   (Followers: 15)
Chinese Economy     Full-text available via subscription   (Followers: 4)
Chinese Journal of Population, Resources and Environment     Open Access  
Chinese Journal of Social Science and Management     Open Access  
Christian University of Thailand Journal     Open Access  
Chulalongkorn Business Review     Open Access  
Ciência & Saúde Coletiva     Open Access   (Followers: 2)
Ciencia, Economía y Negocios     Open Access   (Followers: 1)
Circular Economy and Sustainability     Hybrid Journal   (Followers: 5)
Climate and Energy     Full-text available via subscription   (Followers: 7)
CLIO América     Open Access   (Followers: 2)
Cliometrica     Hybrid Journal   (Followers: 5)
Colombo Business Journal     Open Access  
Community Development Journal     Hybrid Journal   (Followers: 31)
Compendium : Cuadernos de Economía y Administración     Open Access   (Followers: 2)
Compensation & Benefits Review     Hybrid Journal   (Followers: 8)
Competition & Change     Hybrid Journal   (Followers: 12)
Competitive Intelligence Review     Hybrid Journal   (Followers: 3)
Competitiveness Review : An International Business Journal incorporating Journal of Global Competitiveness     Hybrid Journal   (Followers: 5)
Computational Economics     Hybrid Journal   (Followers: 11)
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 9)
Computer Law & Security Review     Hybrid Journal   (Followers: 26)
Computers & Operations Research     Hybrid Journal   (Followers: 15)
Consilience : The Journal of Sustainable Development     Open Access   (Followers: 3)
Construction Innovation: Information, Process, Management     Hybrid Journal   (Followers: 17)
Consumer Behavior Studies Journal     Open Access   (Followers: 1)
Consumer Psychology Review     Hybrid Journal   (Followers: 2)
Contemporary Wales     Full-text available via subscription   (Followers: 1)
Contextus - Revista Contemporânea de Economia e Gestão     Open Access   (Followers: 1)
Continuity & Resilience Review     Hybrid Journal   (Followers: 3)

        1 2 3 4 5 6 7 8 | Last

Similar Journals
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Asia-Pacific Journal of Operational Research
Journal Prestige (SJR): 0.477
Citation Impact (citeScore): 1
Number of Followers: 3  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0217-5959 - ISSN (Online) 1793-7019
Published by World Scientific Homepage  [119 journals]
  • A Real-Time Pricing Scheme with Advertisement Competition Based on
           Multi-Leader–Multi-Follower Game in Smart Community

    • Free pre-print version: Loading...

      Authors: Yeming Dai, Yao Qi, Lu Li, Hongwei Gao
      Abstract: Asia-Pacific Journal of Operational Research, Volume 38, Issue 05, October 2021.
      In this paper, an advertising differential game model is proposed to describe the competition among different power retailers for attracting users in continuous time. After the equilibrium of advertising differential game is obtained, a multi-leader–multi-follower game model is developed to study the real-time pricing scheme in smart community. The power retailers calculate the optimal prices in response to the users’ power consumption and obtain the non-cooperation Nash equilibrium, and then the multi-leader–multi-follower game equilibrium is found. The numerical simulation is performed to discuss the influence of different factors on the payoff of power retailers and users and to verify the rationality of the proposed pricing scheme. The results show that both advertising efficiency and user scale have positive effects on the revenues of the power retailers. Besides, the rise of electricity price has negative effect on users’ utilities, meanwhile it makes the revenues of power retailers increase at first and then decrease. Moreover, power retailers will not transfer advertising costs to the users in the form of incremental electricity price.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-05-29T07:00:00Z
      DOI: 10.1142/S0217595921400236
      Issue No: Vol. 38, No. 05 (2021)
       
  • A Novel Rescheduling Algorithm for the Airline Recovery with Flight
           Priorities and Airport Capacity Constraints

    • Free pre-print version: Loading...

      Authors: Chenlu Ji, Mingang Gao, Xu Zhang, Jiaxuan Li
      Abstract: Asia-Pacific Journal of Operational Research, Volume 38, Issue 05, October 2021.
      Many flights experience delays at the airport due to bad weather, temporary closures of airports, unscheduled maintenance, etc., which emphasizes the urgent need for disruption management. It is widely accepted for Chinese airline companies to determine the flight timetable according to the lexicographic preference of flight priorities. Flight schedulers usually deal with the preceding flights as important as the latter flight of a higher priority. In this paper, we propose a build-in flight feasibility verification algorithm to improve the rescheduling algorithm. A novel model of the feasibility verification problem is given, which is equivalent to the model of a maximum clique problem for networks. Examples and tests show the advantage of our algorithm, and the algorithm runs fairly quickly and can be plugged in other scheduling algorithms easily.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-05-27T07:00:00Z
      DOI: 10.1142/S021759592140025X
      Issue No: Vol. 38, No. 05 (2021)
       
  • An Optimal Online Algorithm for Scheduling with Learning Consideration

    • Free pre-print version: Loading...

      Authors: Ran Ma, Wenwen Han, Cuixia Miao, Juan Zou
      Abstract: Asia-Pacific Journal of Operational Research, Volume 38, Issue 05, October 2021.
      This paper investigates a classic online scheduling problem with learning effect on a single machine. Specifically, a number of independent jobs that arrive online over time will be processed on a single machine and learning effect implies that the real processing time of job [math] is a non-increasing function of its position [math], i.e., [math], where [math] is the basic processing time of job [math] and [math] is the learning index. Our goal is to minimize the total completion time of all jobs. For the problem, we develop a deterministic polynomial time online algorithm called Delayed Shortest Basic Processing Time (DSBPT) and state that it is an online algorithm with a competitive ratio of 2, which matches the lower bound of the online scheduling problem we focus on.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-05-26T07:00:00Z
      DOI: 10.1142/S0217595921400029
      Issue No: Vol. 38, No. 05 (2021)
       
  • V–E Algorithm: A New Vital Vertex Identifying Algorithm Based on
           Vertex–Edge Interaction

    • Free pre-print version: Loading...

      Authors: Haoyu Wang, Xingqin Qi
      Abstract: Asia-Pacific Journal of Operational Research, Volume 38, Issue 05, October 2021.
      Finding vital vertices is an important issue in complex network analysis, which has wide applications in disease control, information diffusion, etc. This topic has attracted increasing attention from various disciplines. In this paper, we propose a new algorithm called Vertex–Edge algorithm to find vital vertices. This algorithm takes both the incident edges and also its neighbors into consideration when evaluating a vertex’s importance, and the importance of vertices and edges construct a mutually updated iterative framework. We also give convergence conditions for the iterative framework. Besides, we verify the stability, effectiveness, accuracy, and superiority of this new Vertex–Edge algorithm by applying it on lots of networks (unweighted or weighted) and comparing the results with other 10 more existing methods. This new method is expected to have promising applications in the future.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-05-26T07:00:00Z
      DOI: 10.1142/S0217595921400133
      Issue No: Vol. 38, No. 05 (2021)
       
  • A Novel Adaptive Differential Privacy Algorithm for Empirical Risk
           Minimization

    • Free pre-print version: Loading...

      Authors: Kaili Zhang, Haibin Zhang, Pengfei Zhao, Haibin Chen
      Abstract: Asia-Pacific Journal of Operational Research, Volume 38, Issue 05, October 2021.
      Privacy-preserving empirical risk minimization model is crucial for the increasingly frequent setting of analyzing personal data, such as medical records, financial records, etc. Due to its advantage of a rigorous mathematical definition, differential privacy has been widely used in privacy protection and has received much attention in recent years of privacy protection. With the advantages of iterative algorithms in solving a variety of problems, like empirical risk minimization, there have been various works in the literature that target differentially private iteration algorithms, especially the adaptive iterative algorithm. However, the solution of the final model parameters is imprecise because of the vast privacy budget spending on the step size search. In this paper, we first proposed a novel adaptive differential privacy algorithm that does not require the privacy budget for step size determination. Then, through the theoretical analyses, we prove that our proposed algorithm satisfies differential privacy, and their solutions achieve sufficient accuracy by infinite steps. Furthermore, numerical analysis is performed based on real-world databases. The results indicate that our proposed algorithm outperforms existing algorithms for model fitting in terms of accuracy.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-05-05T07:00:00Z
      DOI: 10.1142/S021759592140011X
      Issue No: Vol. 38, No. 05 (2021)
       
  • A Strong Convergence Theorem for Solving the Split Equality Fixed Point
           Problem

    • Free pre-print version: Loading...

      Authors: Xueling Zhou, Meixia Li, Haitao Che
      Abstract: Asia-Pacific Journal of Operational Research, Volume 38, Issue 05, October 2021.
      In this paper, we study the split equality fixed point problem and propose a new iterative algorithm with a self-adaptive stepsize that does not need the prior information of the operator norms and is calculated easily. The L-Lipschitz and quasi-pseudo-contractive mappings are chosen as the operators in the algorithm since they have a wider range of applications. Moreover, we prove that the sequence generated by the algorithm strongly converges to the solution of the problem. Finally, we check the feasibility and effectiveness of the algorithm by comparing with other algorithms.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-04-20T07:00:00Z
      DOI: 10.1142/S0217595921400145
      Issue No: Vol. 38, No. 05 (2021)
       
  • On Solving the Convex Semi-Infinite Minimax Problems via Superlinear
           [math] Incremental Bundle Technique with Partial Inexact Oracle

    • Free pre-print version: Loading...

      Authors: Ming Huang, Jinlong Yuan, Sida Lin, Xijun Liang, Chongyang Liu
      Abstract: Asia-Pacific Journal of Operational Research, Volume 38, Issue 05, October 2021.
      In this paper, we study convex semi-infinite programming involving minimax problems. One of the difficulties in solving these problems is that the maximum type functions are not differentiable. Due to the nonsmooth nature of the problem, we apply the special proximal bundle scheme on the basis of [math]-decomposition theory to solve the nonsmooth convex semi-infinite minimax problems. The proposed scheme requires an evaluation within some accuracy for all the components of the objective function. Regarding the incremental method, we only need one component function value and one subgradient which are estimated to update the bundle information and produce the search direction. Under some mild assumptions, we present global convergence and local superlinear convergence of the proposed bundle method. Numerical results of several example problems are reported to show the effectiveness of the new scheme.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-04-20T07:00:00Z
      DOI: 10.1142/S0217595921400157
      Issue No: Vol. 38, No. 05 (2021)
       
  • Smoothing Approximation to the New Exact Penalty Function with Two
           Parameters

    • Free pre-print version: Loading...

      Authors: Jing Qiu, Jiguo Yu, Shujun Lian
      Abstract: Asia-Pacific Journal of Operational Research, Volume 38, Issue 05, October 2021.
      In this paper, we propose a new non-smooth penalty function with two parameters for nonlinear inequality constrained optimization problems. And we propose a twice continuously differentiable function which is smoothing approximation to the non-smooth penalty function and define the corresponding smoothed penalty problem. A global solution of the smoothed penalty problem is proved to be an approximation global solution of the non-smooth penalty problem. Based on the smoothed penalty function, we develop an algorithm and prove that the sequence generated by the algorithm can converge to the optimal solution of the original problem.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-04-09T07:00:00Z
      DOI: 10.1142/S0217595921400108
      Issue No: Vol. 38, No. 05 (2021)
       
  • Distributed Core Decomposition in Probabilistic Graphs

    • Free pre-print version: Loading...

      Authors: Qi Luo, Dongxiao Yu, Feng Li, Xiuzheng Cheng, Zhipeng Cai, Jiguo Yu
      Abstract: Asia-Pacific Journal of Operational Research, Volume 38, Issue 05, October 2021.
      This paper initializes distributed algorithm studies for core decomposition in probabilistic graphs. Core decomposition has been proven to be a useful primitive for a wide range of graph analyses, but it has rarely been studied in probabilistic graphs, especially in a distributed environment. In this work, under a distributed model underlying Pregel and live distributed systems, we present the first known distributed solutions for core decomposition in probabilistic graphs, where there is an existence probability for each edge. In the scenario that the existence probability of edges are known to nodes, the proposed algorithm can get the exact coreness of nodes with a high probability guarantee. The proposed algorithm can also be used to efficiently update the coreness of nodes in dynamic graphs, where a set of edges are inserted/deleted into/from the graph. In the harsher case that the existence probability is unknown, we present a novel method to estimate the existence probability of edges, based on which the coreness of nodes with small approximation ratio guarantee can be computed. Extensive experiments are conducted on different types of real-world graphs and synthetic graphs. The results illustrate that the proposed algorithms exhibit good efficiency, stability and scalability.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-03-22T07:00:00Z
      DOI: 10.1142/S021759592140008X
      Issue No: Vol. 38, No. 05 (2021)
       
  • Randomized Parallel Algorithm for Maximizing Nonsubmodular Function
           Subject to Cardinality Constraint

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      Authors: Jingjing Tan, Wenting Chen, Meixia Li, Wenchao Wang
      Abstract: Asia-Pacific Journal of Operational Research, Volume 38, Issue 05, October 2021.
      The problem of maximization submodular functions with a cardinality constraint has been extensively researched in recent years. Balkanski and Singer were the first to study this class problem. Subsequently, Chekuri and Kent recently extended these results to more general constraints, that is, [math]-cardinality constraint, partition and laminar matroids, matching, knapsack constraints, and including their intersection. They proposed a [math] approximation randomized-parallel-greedy algorithm which are poly-logarithmic adaptivity. However, these existing approaches are hardly extended to the nonsubmodular case. In this paper, we investigate the problem of maximization on a nonsubmodular function subject to a cardinality constraint, provided the objective function is specified by a generic submodularity ratio [math]. We design a [math]-approximation Greedy algorithm by using the technical aspects to maximize the multilinear relaxation of the object function under the [math]-cardinality constraints. The adaptive of multilinear relaxation is [math]; the number of oracle is [math].
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-03-22T07:00:00Z
      DOI: 10.1142/S0217595921400091
      Issue No: Vol. 38, No. 05 (2021)
       
  • A Combinatorial Characterization for Population Monotonic Allocations in
           Convex Independent Set Games

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      Authors: Bin Liu, Han Xiao, Qizhi Fang
      Abstract: Asia-Pacific Journal of Operational Research, Volume 38, Issue 05, October 2021.
      Independent set games are cooperative games defined on graphs, where players are edges and the value of a coalition is the maximum size of independent sets in the subgraph defined by the coalition. In this paper, we study population monotonic allocation schemes for independent set games. For independent set games introduced by Deng et al. [X. Deng, T. Ibaraki and H. Nagamochi (1999). Algorithmic aspects of the core of combinatorial optimization games. Mathematics of Operations Research, 24(3), 751–766], we provide a combinatorial characterization for population monotonic allocation schemes in convex instances. For independent set games introduced by Xiao et al. [H. Xiao, Y. Wang and Q. Fang (2021). On the convexity of independent set games. Discrete Applied Mathematics, 291, 271–276], we prove the equivalence of convexity, population monotonicity and balancedness.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-03-13T08:00:00Z
      DOI: 10.1142/S0217595921400066
      Issue No: Vol. 38, No. 05 (2021)
       
  • Pareto-optimal Algorithms for Scheduling Games on Parallel-batching
           Machines with Activation Cost

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      Authors: Long Zhang, Jiguo Yu, Yuzhong Zhang
      Abstract: Asia-Pacific Journal of Operational Research, Volume 38, Issue 05, October 2021.
      We study one scheduling game with activation cost, where each game involves [math] jobs being processed on [math] parallel-batching identical machines. Each job, as an agent, selects a machine (more precisely, a batch on a machine) for processing to minimize his disutility, which consists of the load of his machine and his share in the machine’s activation cost. We prove that Nash equilibrium may not exist for the scheduling game. We design a polynomial-time algorithm to produce pareto-optimal schedules for two special cases of the scheduling game. Finally, we show that the general form of the scheduling game has pareto-optimal schedule by an improved polynomial-time algorithm, and prove that the schedule is a tight [math]-approximate Nash equilibria.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-03-13T08:00:00Z
      DOI: 10.1142/S0217595921400078
      Issue No: Vol. 38, No. 05 (2021)
       
  • Non-Submodular Maximization with Matroid and Knapsack Constraints

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      Authors: Yijing Wang, Donglei Du, Yanjun Jiang, Xianzhao Zhang
      Abstract: Asia-Pacific Journal of Operational Research, Volume 38, Issue 05, October 2021.
      We investigate the problem of maximizing a [math]-submodular function subject to one or multiple matroid constraints and one knapsack constraint. By the greedy local search technique, we present approximation algorithms with constant approximation ratios. When [math], our model reduces to the regular submodular maximization problem investigated in the literature under the same type of constraints. Our results therefore contribute towards the line of research on constrained non-submodular function maximization.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-03-09T08:00:00Z
      DOI: 10.1142/S0217595921400017
      Issue No: Vol. 38, No. 05 (2021)
       
  • A Semi-Online Algorithm for Single Machine Scheduling with Rejection

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      Authors: Sainan Guo, Ran Ma, Yuzhong Zhang, Baoqiang Fan
      Abstract: Asia-Pacific Journal of Operational Research, Volume 38, Issue 05, October 2021.
      In this paper, a single-machine semi-online scheduling problem with rejection is addressed. In this model, “semi-online” implies that [math], where [math] and [math] are the maximum processing time and the minimum one among all jobs, respectively, [math]. In this setting, each job arrives online over time, and rejection is allowable. Our goal is minimizing the total penalty cost of rejected jobs plus the total completion time of processed jobs. The seminal result of this study is that we offer an algorithm with competitive ratio [math], which matches the result of the problem without rejection.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-03-09T08:00:00Z
      DOI: 10.1142/S0217595921400030
      Issue No: Vol. 38, No. 05 (2021)
       
  • Streaming Algorithms for Maximizing Monotone DR-Submodular Functions with
           a Cardinality Constraint on the Integer Lattice

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      Authors: Zhenning Zhang, Longkun Guo, Yishui Wang, Dachuan Xu, Dongmei Zhang
      Abstract: Asia-Pacific Journal of Operational Research, Volume 38, Issue 05, October 2021.
      Emerging applications such as optimal budget allocation and sensor placement impose problems of maximizing variants of submodular functions with constraints under a streaming setting. In this paper, we first devise a streaming algorithm based on Sieve-Streaming for maximizing a monotone diminishing return submodular (DR-submodular) function with a cardinality constraint on the integer lattice and show it is a one-pass algorithm with approximation ratio [math]. The key idea to ensure one pass for the algorithm is to combine binary search for determining the level of an element with the exponential-growth method for estimating the OPT. Inspired by Sieve-Streaming++, we then improve the memory of the algorithm to [math] and the query complexity to [math].
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-03-09T08:00:00Z
      DOI: 10.1142/S0217595921400042
      Issue No: Vol. 38, No. 05 (2021)
       
  • Study on Low-Carbon Supply Chain Coordination Considering Reference
           Emission Reduction Effect

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      Authors: Fanjun Yao, Hongwei Gao, Hui Jiang, Yunxu Zhou
      Abstract: Asia-Pacific Journal of Operational Research, Volume 38, Issue 05, October 2021.
      This paper documents the first attempt to apply the differential game theory for investigating some properties of a low-carbon supply chain coordination by employing the cost-sharing mechanism. The manufacturer is the brand owner and the corresponding low-carbon goodwill is increased with respect to the reference emission reduction effect and consumption promotion. Three dynamic games are well-studied by considering the multiple effects of price and non-price factors on the market. It can be observed that the manufacturer always prefers to employ the coordination mechanism. When the manufacturer opts for a cost-sharing program, the manufacturer and retailer under Model-D are always economically better off, and therefore a cost-sharing program is always profit-Pareto-improving.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-02-27T08:00:00Z
      DOI: 10.1142/S0217595920400229
      Issue No: Vol. 38, No. 05 (2021)
       
  • Copula Approach to Multivariate Energy Efficiency Analysis

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      Authors: Mervenur Sözen, Mehmet Ali Cengiz
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Data envelopment analysis (DEA) is a method that finds the effectiveness of an existing system using a number of input and output variables. In this study, we obtained energy efficiencies of construction, industrial, power, and transportation sectors in OECD countries for 2011 using DEA. It is possible to achieve the efficiencies in different sectors. However, we aim to find joint energy efficiency scores for all sectors. One of the methods proposed in the literature to obtain joint efficiency is network data envelopment analysis (network DEA). Network DEA treats sectors as sub-processes and obtains system and process efficiencies through optimal weights. Alternatively, we used a novel copula-based approach to achieve common efficiency scores. In this approach, it is possible to demonstrate the dependency structure between the efficiency scores of similar qualities obtained with DEA by copula families. New efficiency scores are obtained with the help of joint probability distribution. Then, we obtained joint efficiency scores through the copula approach using these efficiency scores. Finally, we obtained the joint efficiency scores of the same sectors through network DEA. As a result, we compared network DEA with the copula approach and interpreted the efficiencies of each energy sector and joint efficiencies.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-10-02T07:00:00Z
      DOI: 10.1142/S0217595921500421
       
  • On Exchange Methods for Nonlinear Semi-Infinite Programs

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      Authors: Liping Zhang, Shouqiang Du
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      A new exchange method is presented for semi-infinite optimization problems with polyhedron constraints. The basic idea is to use an active set strategy as exchange rule to construct an approximate problem with finitely many constraints at each iteration. Under mild conditions, we prove that the proposed algorithm terminates in a finite number of iterations and guarantees that the solution of the resulting approximate problem at final iteration converges to the solution of the original problem within arbitrarily given tolerance. Numerical results indicate that the proposed algorithm is efficient and promising.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-09-28T07:00:00Z
      DOI: 10.1142/S0217595921500433
       
  • Single-Machine Due-Window Assignment Scheduling with Resource Allocation
           and Generalized Earliness/Tardiness Penalties

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      Authors: Yu Tian
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      In this study, the due-window assignment single-machine scheduling problem with resource allocation is considered, where the processing time of a job is controllable as a linear or convex function of amount of resource allocated to the job. Under common due-window and slack due-window assignments, our goal is to determine the optimal sequence of all jobs, the due-window start time, due-window size, and optimal resource allocation such that a sum of the scheduling cost (including weighted earliness/tardiness penalty, weighted number of early and tardy job, weighted due-window start time, and due-window size) and resource consumption cost is minimized. We analyze the optimality properties, and provide polynomial time solutions to solve the problem under four versions of due-window assignment and resource allocation function.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-09-08T07:00:00Z
      DOI: 10.1142/S021759592150041X
       
  • Impact of RFID Technology on Coordination of a Three-Tier Fresh Product
           Supply Chain

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      Authors: Qi Zheng, Bin Hu, Tijun Fan, Chang Xu, Xiaolong Li
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      This paper focuses on the impact of radio-frequency identification (RFID) technology adoption on supply chain coordination. We consider a three-tier supply chain consisting of one supplier, one transporter and one retailer with centralized and decentralized decision-making. Considering the factors of RFID tag cost and product freshness, two scenarios — with RFID and without RFID — are analyzed. In the decentralized supply chain, a revenue-sharing contract is established to explore each partner’s decisions on ordering quantity, wholesale price and profits. The results show that (1) the tag cost of RFID has different effects on the pricing decisions, ordering quantity and profit of an FPSC, and if the amount of transportation time compression increases, the range of the tag cost’s boundary value will be wider when adopting RFID technology; (2) when the members of an FPSC choose the optimal wholesale price, optimal initial fare and appropriate revenue-sharing coefficient, the FPSC can achieve a win–win result; and (3) the amount of transportation time compression has a positive correlation with the expected profit of the supplier, transporter and retailer but has a negative correlation with loss of the product.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-08-31T07:00:00Z
      DOI: 10.1142/S0217595921400339
       
  • A Computational Approach to Optimal Control Problems with Almost Smooth
           Controls

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      Authors: Ying Zhang, Zhao Zhang, Yingtao Xu
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      In this paper, we consider a class of optimal control problems involving continuous control and state inequality constraints where the control is almost smooth. We first employ the control parametrization technique via approximating the control signal by a piecewise linear function. Then, we develop a time scaling transformation procedure for transforming the approximate problem into an equivalent problem that can be solved readily using conventional methods. On this basis, a novel exact penalty function method is constructed by appending penalized constraint violations to the cost function. The gradient formulas and convergent properties ensure that the transformed unconstrained optimal parameter selection problems can be solved by existing optimization algorithms or software packages. Finally, an example is solved showing the effectiveness and applicability of the approach proposed.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-08-31T07:00:00Z
      DOI: 10.1142/S0217595921400340
       
  • Demand Information Sharing in the Presence of B2B Spot Market

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      Authors: Shanshan Ma, Liyan Wang
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Companies have started to use a business-to-business (B2B) spot market in combination with their traditional long-term procurement contracts to procure intermediate goods. This study investigates whether or not the market players should share their demand forecast information with one another in a supplier — manufacturer supply chain and assess the benefits of sharing information in the presence of the B2B spot market. First, the supplier and manufacturer make forecast on the demand, and during this period they select an information-sharing arrangement, that is, whether to share information or not. Then, the supplier sets the wholesale price and the manufacturer submits an order after observing the wholesale price. Both the supplier and manufacturer can trade their intermediate goods in a B2B spot market. We find that the manufacturer can infer the supplier’s demand forecast from the wholesale price in the non-information-sharing case, but the supplier cannot enjoy such an advantage. We also find that information sharing benefits both the supplier and the manufacturer, if and only if demand and spot price are positively correlated and the supplier’s expectation of the manufacturer’s forecast is medium. By contrast, obtaining more demand forecast information can hurt supply chain players. Information sharing benefits the manufacturer but hurts the supplier when the supplier’s expectation of the manufacturer’s forecast is high. However, when the supplier’s expectation of the manufacturer’s forecast is low, information sharing benefits the supplier but hurts the manufacturer.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-08-31T07:00:00Z
      DOI: 10.1142/S0217595921500329
       
  • Two-Stage Heuristic Algorithm Proposal for Urban E-Commerce Deliveries

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      Authors: Mehmet Karaoğlu, Gökhan Kara
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      In today’s intensive competition conditions, it is an inevitable necessity for the companies operating in the e-commerce sector to manage their physical distribution processes efficiently and effectively. The most important step in e-commerce logistics processes is the last step delivery operations in the city. In order for these operations to be carried out quickly and efficiently, delivery vehicles and personnel must be optimally led. These problems, referred to as vehicle routing problem (VRP) in the literature, include determining the least cost routes that vehicles will cover to meet customer needs. In this study, the urban delivery problems of the enterprises operating in the online retail sector are examined. In line with these problems, VRP for urban e-commerce deliveries has been modified; open, multi-depot, distribution aggregation, time-window VRP is discussed. A mathematical model for the modified VRP has been developed and a new heuristic algorithm consisting of two stages has been developed for large-scale problems. The developed algorithm was tested on three different cases. The results are compared with the solution of the nearest neighbor method and the performance of the proposed algorithm is presented.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-08-31T07:00:00Z
      DOI: 10.1142/S0217595921500342
       
  • An Iterated Local Search Heuristic for the Staff Scheduling Problem for
           Part-Time Employees in Japan

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      Authors: Wei Wu, Naoaki Katoh, Atsuko Ikegami
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      In this paper, we introduce a mathematical programming model for solving a staff scheduling problem based on one-day duties (task patterns) of individual staff members. The model can accommodate various service types, management policies, and staff preferences. We first enumerate all feasible one-day duties and propose an iterated local search approach that incorporates various methodologies, including a size-reduction method and a very large-scale neighborhood search. For the very large-scale neighborhood search, we design a dynamic programming method that aims to find the most improved schedule and can be used in the rescheduling stage. Computational results show that the model and the proposed algorithm perform well for real-world instances in Japan.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-08-31T07:00:00Z
      DOI: 10.1142/S0217595921500378
       
  • Approximation Algorithms for Non-Submodular Optimization Over Sliding
           Windows

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      Authors: Yunxin Luo, Chenchen Wu, Chunming Xu
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      In this paper, the problem we study is how to maximize a monotone non-submodular function with cardinality constraint. Different from the previous streaming algorithms, this paper mainly considers the sliding window model. Based on the concept of diminishing-return ratio [math], we propose a [math]-approximation algorithm with the memory [math], where [math] is the ratio between maximum and minimum values of any singleton element of function [math]. Then, we improve the approximation ratio to [math] through the sub-windows at the expense of losing some memory. Our results generalize the corresponding results for the submodular case.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-08-31T07:00:00Z
      DOI: 10.1142/S021759592150038X
       
  • Cross-Efficiency Evaluation Method Taking Management Objectives as
           Reference Points from Peer Perspective

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      Authors: Hai-Liu Shi, Sheng-Qun Chen, Ying-Ming Wang, Yan Huang
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      According to the management by objectives (MBO) theory, performance evaluations should take into account the achievement of management objectives (MOs). The most commonly used performance evaluation method — the cross-efficiency evaluation method — seldom considers the role of MOs as a reference point. According to the prospect theory, decision-makers underestimate the benefits that exceed the reference point; they also exaggerate the losses that fall below the reference point. This irrational psychology is more obvious when evaluating the performance evaluation of peers. As such, this paper proposes a cross-efficiency evaluation method based on prospect theory, which takes MOs as a reference point from a peer perspective. First, taking MOs as reference points, a decision-making unit (DMU) chooses a set of weights for each peer, in order to maximize or minimize the prospects of the peer, according to the benevolent or aggressive attitude of the DMU. In order to improve the adaptability of the method, the precise number of MOs is further extended to be an interval number. Finally, the relationship between models, which are based on precise MOs and interval MOs, is illustrated by propositions. Finally, numerical examples are provided to illustrate the applications of the proposed cross-efficiency evaluation method.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-08-31T07:00:00Z
      DOI: 10.1142/S0217595921500408
       
  • Technology-Driven Supply Chain Management with OR Applications in
           Industrial 4.0 Era

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      Authors: Bin Shen, Ciwei Dong, Chi To Ng
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      In industrial 4.0 era, many advanced technologies, such as blockchain, advanced robotics, additive manufacturing, the Internet of Things, machine learning, and artificial intelligence, have received considerable attention in industry and academia. In real practice, such technologies have been implemented by firms, and they play an important role in increasing the operational efficiency of the firms as well as the whole supply chain through Operational Research (OR) methods. Thus, it is critical to consider the impacts of advanced technologies on supply chain management with OR applications. This special issue explores new practices and applications of technology-driven supply chain management in Industry 4.0. This editorial note summarizes the discussions on applications of different technologies in supply chains. Moreover, we list important future research directions based on contributed papers.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-08-20T07:00:00Z
      DOI: 10.1142/S0217595921020036
       
  • A Replenishment Inventory Model with a Stock-Dependent Demand and
           Age–Stock-Dependent Cost Functions in a Random Environment

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      Authors: Yonit Barron
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      This paper investigates an [math] continuous-review perishable inventory model with a stock-dependent Poisson demand process, full backordering (with an extension for lost sales) and uncertainty in lead time and shelf life. Four types of costs are considered: a fixed cost of an order and each outdated item; age-dependent costs of an item (i.e., holding and salvage costs), given by a function of its remaining shelf life; and a delay cost of a backlogged demand unit, which is a function of its delay duration. Applying the supplementary variable technique, we obtain the joint probability-density function of the number of items in the system and the remaining time and thereby obtain the optimal parameters minimizing the long-run average total cost. Numerical experiments show that supply chain profits are enhanced by integrating the age components into replenishment decisions, and ignoring the shelf age- and delay-dependent costs may result in a substantial loss (up to 25%). It further appeared that estimating the lead-time distribution by an exponential one is significantly more costly, in particular as the c.v. differs from 1. In contrast, an exponential shelf life may provide a good heuristic for other shelf-life distributions.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-08-20T07:00:00Z
      DOI: 10.1142/S0217595921500354
       
  • Iterative Multi-Attribute Procurement Auction with Decision Support for
           Bid Formulation

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      Authors: T. G. Chetan, Mamata Jenamani, S. P. Sarmah
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Iterative multi-attribute reverse auctions in practice create certain difficulties for both the buyer and participating bidders. While the buyer faces the problem of creating the right attribute weights, the bidders have difficulty in adjusting the attribute values in each round. In this paper, we present an iterative multi-attribute reverse auction mechanism based on integrated data envelopment analysis (DEA) and best–worst method (BWM) with an objective of reducing the intervention of the buyer in the determination of the winner and also easing up the preference elicitation process. Unlike the typical scoring auctions, the proposed mechanism does not require the buyer to estimate the characteristics of the participating sellers in order to determine the optimal scoring function. As there will be no other intervention from the buyer during the winner determination process, the proposed method makes the procurement process impartial and corruption-free. Besides solving the buyer’s problem, the proposed mechanism is also associated with an optimal bid determination method (OBDM) to assist the sellers in formulating improvised bids in iterative rounds of the auction. Simulation experiments show that the proposed OBDM benefits both the buyer and sellers. For the buyer, it provides higher expected utility and attribute values as per his preferences; for the seller, it gives a better expected profit and a higher probability of winning.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-08-16T07:00:00Z
      DOI: 10.1142/S0217595921500366
       
  • Online Pricing Strategy with Considering Consumers’ Fairness
           Concerns

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      Authors: Liu Yang, Yuanyuan Zheng, Jiasi Fan, Shaozeng Dong
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      The development of emerging technologies, such as advanced information system, social media, and blockchain, has significantly changed consumers’ behaviors in relation to online purchase. Having access to the historical price information, consumers are able to compare the current price with the historical prices and may raise fairness concerns in the comparison process. We investigate the impacts of consumers’ fairness concerns on retailers’ pricing strategies in a two-stage model. We show that when the retailer uses uniform pricing strategy, consumers’ fairness concerns induce the retailer to decrease product price. As a consequence, the market demand expands and the retailer’s profit reduces. When the retailer adopts multi-stage pricing strategy, we find that consumers’ fairness concerns are not always harmful to the retailer’s profit. Under certain conditions, the retailer can benefit from consumers’ fairness concerns. Particularly, the product price in the first period increases, but the price in the second period and the market demand could be increased or decreased, depending on the situations.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-08-06T07:00:00Z
      DOI: 10.1142/S0217595921400327
       
  • An Ordinal Weighted EDM Model for Nonmetric Multidimensional Scaling

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      Authors: Qing-Na Li, Chi Zhang, Mengzhi Cao
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Multidimensional scaling (MDS) is to recover a set of points by making use of noised pairwise Euclidean distances. In some situations, the observed Euclidean distances may contain large errors or even missing values. In such cases, the order of the distances is far more important than their magnitude. Non-metric multidimensional scaling (NMDS) is then to deal with this problem by taking use of the ordinal information. The challenge of NMDS is to tackle the large number of ordinal constraints on distances (for [math] points, this will be of [math]), which will slow down existing numerical algorithms. In this paper, we propose an ordinal weighted Euclidean distance matrix model for NMDS. By designing an ordinal weighted matrix, we get rid of the large number of ordinal constraints and tackle the ordinal constraints in a soft way. We then apply our model to image ranking. The key insight is to view the image ranking problem as NMDS in the kernel space. We conduct extensive numerical test on two state-of-the-art datasets: FG-NET aging dataset and MSRA-MM dataset. The results show the improvement of the proposed approach over the existing methods.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-08-06T07:00:00Z
      DOI: 10.1142/S0217595921500330
       
  • Proximal Gradient-Type Algorithms for a Class of Bilevel Programming
           Problems

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      Authors: Dan Li, Shuang Chen, Li-Ping Pang
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      A class of proximal gradient-type algorithm for bilevel nonlinear nondifferentiable programming problems with smooth substructure is developed in this paper. The original problem is approximately reformulated by explicit slow control technique to a parameterized family function which makes full use of the information of smoothness. At each iteration, we only need to calculate one proximal point analytically or with low computational cost. We prove that the accumulation iterations generated by the algorithms are solutions of the original problem. Moreover, some results of complexity of the algorithms are presented in convergence analysis. Numerical experiments are implemented to verify the efficiency of the proximal gradient algorithms for solving this kind of bilevel programming problems.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-08-06T07:00:00Z
      DOI: 10.1142/S0217595921500391
       
  • Equilibrium Pricing, Advertising, and Quality Strategies in a Platform
           Service Supply Chain

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      Authors: Yong He, Yanan Yu, Zhongyuan Wang, Henry Xu
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Online-to-Offline service platforms are rising with the development of e-commerce and the increasing need for service. Taking the hospitality and tourism industries as typical examples, this paper considers a platform service supply chain, where a leading hotel is responsible for offline service, and a following platform is in charge of pricing, online service, and advertising investment. Three decision modes (i.e., decentralized, cost-sharing, and integrated) for the platform service supply chain are investigated. We derive the optimal service levels for the hotel and the platform, advertising investment, and retail price in each mode. Our analyses indicate that perceived service quality and brand image vary over time, and they gradually converge to a steady-state. The cost-sharing mode can be achieved if the hotel can obtain enough profit per unit. Once the cost-sharing mode is achieved, it can help improve perceived service quality and brand image, which further increases both the hotel and the platform’s profits. However, the integrated mode generates the best-perceived service quality, brand image, supply chain performance, and the lowest price.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-07-16T07:00:00Z
      DOI: 10.1142/S0217595921400315
       
  • Study on Agent Incentives for Resource Sharing on P2P Networks

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      Authors: Yukun Cheng, Xiaotie Deng, Yuhao Li
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      There have recently been extensive studies on proportional response protocol, which is motivated by the successful BitTorrent system for file sharing over a P2P network. The proportional response protocol has been proved to be strategy-proof against weight cheating attacks and edge cheating attacks, in order to allocate a single type of resource on P2P networks. This strategy-proof property holds due to an elegant combinatorial structure: the bottleneck decomposition of the underlying network structure, and the utility function, defined as the total resources that one agent receives from its neighbors. However, Sybil attacks, under which an agent may form several fictitious players and split its resource among them, have been shown as a more difficult attack to defend against, and thus a strategic agent playing Sybil attacks may result in personal gain. Previous efforts have been made to show that an agent may generate a gain, but with limited gains by Sybil attacks on several special networks, including trees, cliques, and rings. This paper is the first to study the agent’s incentives by adopting a Sybil attack on general networks. The main contribution is to prove that any agent cannot obtain more than three times as much as the revenue when it plays honestly.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-07-16T07:00:00Z
      DOI: 10.1142/S0217595921500317
       
  • Cooperative Promotion of Cross-Market Firms Adopting 3D Printing
           Technology

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      Authors: Ke Yan, Guowei Hua, T. C. E. Cheng
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Traditionally, firms often run independent promotional activities to attract consumers and improve their competitiveness. With the rapid development of three-dimensional (3D) printing, also known as additive manufacturing, a growing number of firms in different markets cooperate to conduct cooperative promotion to meet consumer demand. Different from independent promotion, which means that firms promote their products through their individual promotional activities, when they carry out cooperative promotion, in addition to their individual promotional activities, they also carry out a series of cooperative promotional activities to promote their products. For such cross-market cooperation, it is of importance to consider the unit cost of production and the promotion cost to achieve competitive advantage and sustainability of the supply chain. We develop game-theoretic models to investigate the factors that make firms pursue cooperative promotion and how cooperative promotion affects their optimal decisions. We find that whether or not the firms join cooperative promotion mainly depends on the impacts of price, individual promotional activities, and cooperative promotional activities on demand, as well as the unit cost of production. Whether or not firms are willing to make more contribution to cooperative promotion depends on the difference between the efforts of individual promotional activities and cooperative promotional activities. In addition, as the consumer demand for the product increases, the firms will also increase their investments in cooperative and independent promotional activities. Moreover, as the unit cost of production and the impact of cooperative promotional activities on demand change, pursuing cooperative promotion is not necessarily more profitable than pursuing independent promotion.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-07-07T07:00:00Z
      DOI: 10.1142/S0217595921400285
       
  • How to Escape Supply Chain Dilemmas' Manufacturer Encroachment and
           Supplier Cost-Reduction Investment

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      Authors: Qijun Wang, Jiajia Nie, Senmao Xia
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Component suppliers and manufacturers in a supply chain have long faced different dilemmas. The component supplier intends to adopt new technologies to reduce production costs, but the new technologies usually require significant investment costs. The encroachment into retailing can bring more revenue to manufacturers, but the significant costs of establishing and maintaining direct channels and the potential conflicting interests with the retailer might discourage the manufacturer’s encroachment. This study aims to address these dilemmas facing the component supplier and manufacturer by investigating an interesting scenario in which they both can obtain benefits. Within the given context, the manufacturer’s encroachment increases the order of the components, which motivates the supplier to make more technological investments to reduce production costs. The reduction of component costs enables suppliers and manufacturers to reduce the wholesale prices of components and final products. In this case, the manufacturer’s encroachment can benefit both the manufacturer and the retailer. This study is one of the first to investigate how the interaction between the manufacturer and supplier helps solve their respective dilemmas and provide benefits to the whole supply chain. Additionally, we extend the literature on manufacturer encroachment on retailers by considering supplier investment in cost-reduction production.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-07-07T07:00:00Z
      DOI: 10.1142/S0217595921400303
       
  • Evolutionary Game Models of Cooperative Strategies in Blockchain-Enabled
           Container Transport Chains

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      Authors: Zhi-Hua Hu, Ya-Jing Dong
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      This paper describes the interaction between major and auxiliary container transport carriers (MCs and ACs) by using evolutionary game theory models, enabling them to cooperate and share information under sufficient penalties and incentives. The MCs are generally logistics service integrators, mega shipping companies, and port authorities, which affect the regulations and technology innovation much, while the ACs are rest carriers and logistics service providers. Evolutionary games are used to study the cooperative behavior between MCs and ACs in the shipping industry. As indicated by analytical studies, the cooperation between MCs and ACs will be invalid without introducing blockchain technology for adequate supervision. In peak season, an evolutionary equilibrium incurs between MCs and ACs under cooperation or non-cooperation behavior strategies. However, in off-seasons, the evolutionary equilibrium is unique in which both parties choose not to cooperate. When introducing blockchain technology for supervision, the carriers will cooperate in peak and off-seasons. Besides, through a simulation analysis of the established models, the results show that the introduction of blockchain technology can enable carriers to form cooperative alliances, resolve inefficient operations, and achieve a long-term stable equilibrium strategy. We can also apply the results for reference to the regional shipping industry.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-07-05T07:00:00Z
      DOI: 10.1142/S0217595921400297
       
  • Parallel Machine Scheduling with Due Date-to-Deadline Window, Order
           Sharing and Time Value of Money

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      Authors: Yinfeng Xu, Rongteng Zhi, Feifeng Zheng, Ming Liu
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Motivated by a variety of applications in sharing economy, we study an identical parallel machine scheduling problem with due date-to-deadline window by jointly considering machine sharing and the time value of money. A factory owns a set of parallel identical machines and processes a set of production orders within a finite time period. In the sharing setting, the factory may also rent external machines to handle a part of orders by paying some extra cost. The factory aims to determine the sharing policy of the production orders and the scheduling rule of machines, to maximize its total future value of profits by satisfying the orders. To the best of our knowledge, there are no previous results for this problem. In this work, a mathematical programming model is derived, and a problem-specific genetic algorithm and a heuristic are proposed to solve large-scale instances. Numerical experiments using randomly generated instances are carried out to evaluate the effectiveness and efficiency of the proposed solution methods.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-06-28T07:00:00Z
      DOI: 10.1142/S021759592150024X
       
  • A Bicriteria Approach for Saving a Path Maximizing Dynamic Contraflow

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      Authors: Hari Nandan Nath, Stephan Dempe, Tanka Nath Dhamala
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      The maximum dynamic contraflow problem in transportation networks seeks to maximize the flow from a source to a sink within a given time horizon with a possibility of arc reversals. This may result into blockage of paths of desired length from some node of the network towards the source. In some cases such as the evacuation planning, we may require a path towards the source to move some facilities, for example, emergency vehicles. In this work, we model the problem of saving such a path as a bicriteria optimization problem which minimizes the length of the path and maximizes the dynamic flow with arc reversals. We use the [math]-constraint approach to solve the problem and propose a procedure that gives the set of all Pareto optimal solutions in a single-source-single-sink network with integer inputs. We also present computational performance of the algorithm on a road network of Kathmandu city, and on randomly generated networks. The results are of both theoretical and practical importance.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-06-28T07:00:00Z
      DOI: 10.1142/S0217595921500275
       
  • Efficiency Loss and Coordination in the Online Shopping Supply Chain with
           Competitive Shipping Companies

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      Authors: Yihong Hu, Qiang Qiang
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      This paper studies efficiency loss and coordination mechanism in a supply chain with one online retailer and multiple competitive shipping companies in the presence of congestion effects. We build a three-level game between customers, shipping companies and the retailer. The equilibrium market structure is determined. The optimal volume–investment ratio for each shipping company is the same for both centralized and decentralized supply chains, and it is dependent on the delivery time function, independent of competitors’ decisions. The efficiency loss of the decentralized supply chain with one retailer and one shipping company is found to be 1/4, independent of the delivery time function and the demand function. The loss is reduced when competition is introduced into shipping companies and an upper bound of efficiency loss with multiple homogeneous shipping companies is derived. Revenue-sharing contracts may be designed to allow the decentralized supply chain to perform as well as a centralized one. The necessity of coordination is reduced when competition is introduced and the number of competitive companies increases. Finally, we extend the model to consider heterogeneous shipping companies and find that the disparity between shipping companies increases the efficiency loss because in the decentralized supply chain less efficient shipping companies also provide service. This research explicates the relationship options between e-commerce retailers and shipping companies, providing managerial insights for industry practitioners.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-06-21T07:00:00Z
      DOI: 10.1142/S0217595921500251
       
  • On the Quasiconcave Multilevel Programming Problems

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      Authors: H. Sadeghi, M. Esmaeili
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Multilevel programming appears in many decision-making situations. Investigation of the main properties of quasiconcave multilevel programming (QCMP) problems, to date, is limited to bilevel programming (only two levels). In this paper, first, we present an extension of the properties of quasiconcave bilevel programming (QCBP) problems for the case when three levels exist. Then, by induction on [math] (the number of levels), we prove the existence of an extreme point of the polyhedral constraint region that solves the QCMP problem under given conditions. Ultimately, a number of numerical examples are illustrated to verify the results.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-06-21T07:00:00Z
      DOI: 10.1142/S0217595921500263
       
  • An Efficient Elite-Based Simulation–Optimization Approach for Stochastic
           Resource Allocation Problems in Manufacturing and Service Systems

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      Authors: Chun-Chih Chiu, James T. Lin
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Stochastic resource allocation problems (SRAPs) involve determining the optimal configuration of a limited resource to achieve an objective function under given constraints and random effects in manufacturing systems (MSs) and service systems (SSs). The problems are traditionally solved by determining the optimal solution. It is generally preferable to determine as many global optima as possible, or at least a small set of diverse but good candidates, to help the decision-maker rapidly adopt alternative solutions from the set if one solution is unsuitable. However, many local or global optima occur in SRAPs in MSs and SSs due to the interaction between random system factors, such as processing time uncertainty and machine failure rates. Thus, enhancing the searching efficiency of algorithms for SRAPs is a challenge. This study proposes an efficient simulation–optimization approach, called elite-based particle swarm optimization (EPSO), using an optimal replication allocation strategy (ORAS) (i.e., EPSO[math], to address three types of SRAPs from the literature. Three simulation models were constructed to evaluate the system performance under random factors. We developed a novel EPSO to explore and exploit the solution space. We created an elite group (EG) that includes multiple solutions, and each solution of the EG has a statistically nonsignificant difference from the current optimal solution. The new feature of EPSO updates the velocity and position of the particles in the design space based on multiple global optima from the EG to enhance diversity and prevent premature convergence. We propose an ORAS to allocate a limited number of replications to each solution. Three numerical experiments were performed to verify the effectiveness and efficiency of EPSO[math] compared with other simulation–optimization approaches, namely particle swarm optimization (PSO) and the genetic algorithm (GA) with both optimal computing budget allocation (OCBA) and the ORAS. The experimental results reveal that the solution quality of EPSO improved compared with that of PSO and GA, and the ORAS provides a more efficient allocation of the number of replications compared with the OCBA in the three experiments. Finally, the proposed approach also provides an elite set at the end of the algorithm, instead of a single optimal solution, to support decision-making.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-06-21T07:00:00Z
      DOI: 10.1142/S0217595921500305
       
  • The Incentive Study in the Blockchain Era: A Two-Period Strategic
           Inventory Game

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      Authors: Jianheng Zhou, Qingying Li
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      In this paper, we conduct an incentive study on the adoption of the blockchain technology in a two-period model with retailer’s use of strategic inventory. Without the adoption of the blockchain technology, the retailer has private information regarding the market size. We investigate the retailer’s voluntary signaling decisions via his pricing and strategic inventory decisions. We determine the retailer’s equilibrium price and the manufacturer’s optimal wholesale price. Both separating and pooling equilibria are discussed, and the unique lexicographically maximum sequential equilibrium is identified. With the adoption of the blockchain technology, there is no information asymmetric between the supply chain members. We find that the manufacturer has the incentive to adopt the blockchain technology when the demand uncertainty is moderate to high, and the retailer has the incentive to adopt the blockchain technology when the demand uncertainty is low or high. When the manufacturer and the retailer have a misalignment in the adoption of the technology, a central planner can help to achieve coordination.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-06-16T07:00:00Z
      DOI: 10.1142/S0217595921400248
       
  • Fritz John Optimality Conditions for Interval-Valued Multi-Objective
           Functions Using gH-Symmetrical Derivative

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      Authors: Sachin Rastogi, Akhlad Iqbal, Sanjeev Rajan
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      In this paper, we introduce the concept and applications of gH-symmetrical derivative for interval-valued multi-objective functions, which is the generalization of generalized Hukuhara derivative (gH-derivative). By a suitable example it has been shown that gH-symmetrically derivative is an extension of gH-derivative. Furthermore, we apply this new derivative to investigate the Fritz John type optimality conditions for interval-valued multiobjective programming problems. We use LR type of order relation in this context.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-06-16T07:00:00Z
      DOI: 10.1142/S0217595921500299
       
  • Tensor Manifold with Tucker Rank Constraints

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      Authors: Shih Yu Chang, Ziyan Luo, Liqun Qi
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Low-rank tensor approximation plays a crucial role in various tensor analysis tasks ranging from science to engineering applications. There are several important problems facing low-rank tensor approximation. First, the rank of an approximating tensor is given without checking feasibility. Second, even such approximating tensors exist, however, current proposed algorithms cannot provide global optimality guarantees. In this work, we define the low-rank tensor set (LRTS) for Tucker rank which is a union of manifolds of tensors with specific Tucker rank. We propose a procedure to describe LRTS semi-algebraically and characterize the properties of this LRTS, e.g., feasibility of tensors manifold, the equations/inequations size of LRTS, algebraic dimensions, etc. Furthermore, if the cost function for tensor approximation is polynomial type, e.g., Frobenius norm, we propose an algorithm to approximate a given tensor with Tucker rank constraints and prove the global optimality of the proposed algorithm through critical sets determined by the semi-algebraic characterization of LRTS.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-06-11T07:00:00Z
      DOI: 10.1142/S0217595921500226
       
  • Min–Max Scheduling of Batch or Drop-Line Jobs Under Agreeable
           Release and Processing Times

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      Authors: Yuan Gao
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      We study the Pareto optimization scheduling on an unbounded parallel-batch machine with jobs having agreeable release dates and processing times for minimizing makespan and maximum cost simultaneously. The jobs considered in this paper are of two types: batch jobs and drop-line jobs. For batch jobs, the completion time of a job is given by the completion time of the batch containing this job. For drop-line jobs, the completion time of a job is given by the starting time of the batch containing this job plus the processing time of this job. For both of batch jobs and drop-line jobs, we present polynomial-time algorithms for finding all Pareto optimal points.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-06-11T07:00:00Z
      DOI: 10.1142/S0217595921500238
       
  • Herding Behavior and Liquidity in the Cryptocurrency Market

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      Authors: Sonia Arsi, Khaled Guesmi, Elie Bouri
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      In view of explosive trends and excessive trades in the cryptocurrency markets, this paper contributes to the existing literature by bringing in the limelight the effect of liquidity on the herding behavior in the cryptocurrency market. Results from a first applied herding model including contemporaneous and lagged squared market returns demonstrated that market-wide herding exists within falling markets. The incorporation of liquidity highlights further evidences on herding behavior across cryptocurrencies during high and low liquid days, which varies across percentiles. Our findings bring handy implications for topics of portfolio and risk management, as well as regulation.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-06-08T07:00:00Z
      DOI: 10.1142/S0217595921400212
       
  • Self-Adaptive Inertial Projection and Contraction Algorithm for Monotone
           Variational Inequality

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      Authors: Xue Gao, Xingju Cai, Xueye Wang
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      In this paper, we propose a self-adaptive inertial projection and contraction algorithm, by combining backtracking search with the inertial projection and contraction algorithm, for solving monotone variational inequality in Hilbert space. This algorithm not only circumvents the restrictive assumption of Lipschitz continuity of the operator, but also gives more suitable and feasible parameters. Under the assumption that the operator is continuous and monotone, we establish weak convergence for proposed algorithm. Finally, we report some preliminary computational results to show the efficiency and advantage of the algorithm.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-06-08T07:00:00Z
      DOI: 10.1142/S0217595921500214
       
  • Berth Allocation in Transshipment Ports by Considering Quay Crane Coverage
           and Ship Fuel Consumption

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      Authors: Shucheng Yu, Bochen Wang, Si Zhang, Lu Zhen
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      This study investigates an integrated model for the continuous berth allocation and quay crane scheduling problem by considering quay crane coverage range, ship fuel consumption, and transshipment costs. A nonlinear mixed-integer programming model is proposed. Some nonlinear parts in this model are linearized by approximation approaches. While the objective function aims to minimize waiting costs, it also seeks to minimize fuel consumption costs from the current port to the next port and housekeeping costs generated by transshipment between vessels. A local branching-based solution algorithm is designed to solve the proposed model. Computational experiments are conducted to validate the effectiveness of the proposed scientific programming model and efficiency of the algorithm.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-06-08T07:00:00Z
      DOI: 10.1142/S0217595921500287
       
  • When and How Should Cross-Border Platforms Manage Blockchain Technology in
           the Presence of Purchasing Agents'

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      Authors: Xiutian Shi, Shuning Yao, Yizhong Ma
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Copycat issues and unreliable purchasing agents have challenged cross-border consumption and hurt the brands and online platforms significantly. We explicate a setting in which a platform orders from a brand, then sells and competes with the purchasing agents in an overseas market. Worried about the copycat issues, consumers undertake risk when purchasing from both platforms and agents. The blockchain adoption may help release this uncertainty by purchasing from a platform. We show the values and impacts of this new technology on the platform, brand and consumers. It is interesting to observe that the platform does not always have incentive to adopt blockchain, even if it is costless. In the presence of blockchain, we show that the revenue sharing, two-part tariff and profit sharing contracts can achieve supply chain coordination, but the cost sharing contract fails to do so. In the extended models, we discuss what will happen when the brand decides domestic retail price and the platform links optional information nodes to blockchain.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-05-17T07:00:00Z
      DOI: 10.1142/S0217595921400200
       
  • Merging Decision-Making Units with Fuzzy Data

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      Authors: Saeid Ghobadi, Khosro Soleimani-Chamkhorami
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      This paper studies the problem of target setting for a generated entity from a merger among two or more decision making units. Identification of the inherited input/output levels from merging decision-making units is an important issue. In this study, a novel inverse data envelopment analysis model is introduced for target setting of a merger in the presence of fuzzy data. This model enables the merged unit to recognize the required input/output levels from merging units to achieve a predefined efficiency target. Moreover, a fuzzy linear programming model is presented for estimating the minimum attainable efficiency score through a given merging. Then, the performance of the proposed method is examined through a banking application.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-05-11T07:00:00Z
      DOI: 10.1142/S0217595921400121
       
  • Cooperative Decision Making of Supply Chain Members of Shipping Logistics
           Services Under the Background of Blockchain

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      Authors: Yujing Chen, Bin Yang
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      The supply chain of shipping logistics services is an important branch of logistics service supply chain. To ensure the effective operation of the supply chain and to solve problems such as asymmetric information, difficult data quality assurance, and uncontrollable transportation in shipping logistics services, blockchain technology are proposed to reduce information interaction problems. In view of the factors of information sharing and customers’ sensitivity to information quality, a tripartite evolutionary game model with the shipping company, the port and the freight forwarder as the research objects was established, and the cooperative decision making of node companies was discussed before and after the application of blockchain technology. Theoretical derivation and data analysis show that ports and freight forwarder in the supply chain of shipping logistics services dominated by shipping companies are less affected by information sharing and customers’ sensitivity to information quality. With the increase in the application of blockchain technology, when customers have lower expectations for information quality, shipping companies are more willing to cooperate actively. The willingness to cooperate actively between ports and shipping companies is increasing faster than when blockchain technology is not used. Therefore, shipping companies should encourage the active use of blockchain technology to reduce the degree of information sharing between ports and freight forwarder and the influences of customer expectations on shipping companies.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-05-11T07:00:00Z
      DOI: 10.1142/S0217595921400182
       
  • Variable Neighborhood Descent for Multi-Compartment and Multi-Objective
           Vehicle Routing Problem in Refined Product Distribution

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      Authors: Xuping Wang, Wenping Fan, Hongxin Zhan, Zilai Sun
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Refined product distribution is an application of the Multi-compartment Vehicle Routing Problem (MCVRP), which simultaneously considers the vehicle routing, the assignment of heterogonous vehicles and loading policies of multi-compartment. First, we develop an optimization model with the objective of delivering on-time and minimizing transportation cost. Then we propose a Multi-objective Variable Neighborhood Descent Algorithm (MOVND), where the [math]-constraint method transforms the original problem into a series of sub-problems of single objective with constraints. Finally, the efficiency of the proposed algorithm is verified by conducting a large number of small and large instances. Mainly including (i) compared with the classical NSGA-2 algorithm for multi-objective VRP, MOVND provides better performance in terms of convergence, spread and distribution; (ii) the multi-compartment vehicles are able to carry a variety of products simultaneously, which can improve the effective utilization of vehicle space and meet the needs of different customers in a single transportation. In addition, heterogonous vehicles that take full advantage of the characteristics of different vehicles are superior to homogeneous ones in terms of operating cost in the practice of the refined product distribution.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-05-11T07:00:00Z
      DOI: 10.1142/S0217595921500196
       
  • B-Subdifferentials of the Projection onto the Generalized Simplex

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      Authors: Youyicun Lin, Shenglong Hu
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      In this paper, a complete characterization of the B-subdifferential of the projection onto the generalized simplex is given. This work is accomplished with the help of Han–Sun Jacobian, whose full characterization is also given in this case. The characterizations are given with simple and explicit formulae in terms of the active index set of the projection.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-05-11T07:00:00Z
      DOI: 10.1142/S0217595921500202
       
  • Price and Product Quality Decisions for a Two-Echelon Supply Chain in the
           Blockchain Era

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      Authors: Zhongmiao Sun, Qi Xu, Baoli Shi
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Frequent problems of counterfeiting have spawned consumer demands to monitor the entire supply chain. The application of blockchain technology with anti-counterfeiting and traceability can improve the reliability and authenticity of product information and eliminate consumer doubts about product quality. Furthermore, based on the transparency of blockchain technology, brand suppliers can independently obtain the market demand information through information sharing. This paper introduces a consumer suspicion coefficient to illustrate the application of blockchain technology in the supply chain. Considering product authenticity verification and information sharing, we study the optimal pricing and product quality decisions in a two-level supply chain under the following three scenarios: (1) no blockchain technology, a traditional supply chain, and no information sharing (case TN); (2) no blockchain technology but a traditional supply chain with information sharing (case TS); and (3) a supply chain based on blockchain technology (case BT). We find that when the consumer suspicion coefficient increases, consumers will have limited faith in the authenticity of the product, which will affect the retailer’s optimal decision and profit. By comparing the equilibrium results of several cases, we also find that demand information sharing by the retailer may not achieve a win-win outcome in a decentralized channel in the absence of blockchain technology. Under demand information sharing based on blockchain technology, however, if the consumer suspicion coefficient exceeds a certain threshold, the brand supplier and retailer can achieve a win–win outcome. In addition, the extended models reveal that in a centralized supply chain, regardless of the state of market demand, blockchain technology can always improve product quality and retail price and optimize supply chain profit.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-05-05T07:00:00Z
      DOI: 10.1142/S0217595921400169
       
  • Feature Transformation for Corporate Tax Default Prediction: Application
           of Machine Learning Approaches

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      Authors: Mohammad Zoynul Abedin, M. Kabir Hassan, Imran Khan, Ivan F. Julio
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Applications of machine learning (ML) and data science have extended significantly into contemporary accounting and finance. Yet, the prediction and analysis of taxpayers’ status are relatively untapped to date. Moreover, this paper focuses on the combination of feature transformation as a novel domain of research for corporate firms’ tax status prediction with the applicability of ML approaches. The paper also applies a tax payment dataset of Finish limited liability firms with failed and non-failed tax information. Seven different ML approaches train across four datasets, transformed to non-transformed, that effectively discriminate the non-default tax firms from their default counterparts. The findings advocate tax administration to choose the single best ML approach and feature transformation method for the execution purpose.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-05-05T07:00:00Z
      DOI: 10.1142/S0217595921400170
       
  • Applying Simulation Optimization for Agile Vehicle Fleet Sizing of
           Automated Material Handling Systems in Semiconductor Manufacturing

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      Authors: Kuo-Hao Chang, Robert Cuckler
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Automated material handling systems (AMHS) have been widely used in semiconductor manufacturing. However, the performance of AMHS heavily hinges on vehicle fleet sizing, which is a complex yet crucial problem. For example, a small fleet size may increase the average wait time, but a large fleet size can also result in traffic congestion. This tradeoff is difficult and can be further exacerbated by profound uncertainty in the manufacturing process. In the literature, the existing models are focused on improving the mean-based performance of AMHS, where the resulting optimal vehicle fleet size is fixed, lacking the ability and flexibility to respond to the changes and/or special requirements that suddenly come up in the manufacturing process. Another drawback with the existing models is that they are not able to characterize the upside/downside risks associated with the resulting vehicle fleet size. This paper, motivated by a real project, presents a novel quantile-based decision model to fill the gap. The adjustment of [math] values in the proposed decision model allows for agile vehicle fleet sizing according to the production situations, resulting in the satisfactory performance of AMHS. We develop a simulation optimization solution method, called ES-AMHS in short, to enable the efficient derivation of the optimal vehicle fleet size. A comprehensive numerical analysis is conducted to evaluate the efficiency and efficacy of the solution method. Finally, an empirical study in cooperation with a wafer fab in Taiwan is presented to show the practical usefulness of this methodology in a real-world setting.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-05-05T07:00:00Z
      DOI: 10.1142/S0217595921500184
       
  • Portfolio Selection with Regularization

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      Authors: Ning Zhang, Jingnan Chen, Gengling Dai
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      We study the Markowitz mean-variance portfolio selection model under three types of regularizations: single-norm regularizations on individual stocks, mixed-norm regularizations on stock groups, and composite regularizations that combine the single-norm and mixed-norm regularizations. With mixed-norm regularizations incorporated, our model can accomplish group and stock selections simultaneously. Our empirical results using both US and global equity market data show that compared to the classical mean-variance portfolio, almost all regularized portfolios have better out-of-sample risk-adjusted performance measured by Sharpe ratio. In addition, stock selection and group screening accomplished by adding [math] and [math] regularizations respectively can lead to decreased volatility, turnover rate, and leverage ratio. Yet there are instances in which diversifying across different groups is more favorable, depending on the grouping methods. Moreover, we find a positive correlation between portfolio turnover and leverage. Heavily leveraged portfolios also have high turnover rates and thus high transaction costs.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-04-26T07:00:00Z
      DOI: 10.1142/S0217595921500160
       
  • Single-Machine Scheduling Problems with Variable Processing Times and
           Past-Sequence-Dependent Delivery Times

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      Authors: Ji-Bo Wang, Jing Xue, Bo Cui, Ming Gao
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Scheduling problems with variable processing times and past-sequence-dependent delivery times are considered on a single-machine. The delivery times of jobs depend on their waiting times of processing. A job’s actual processing time depends on its position in a sequence, its starting time and its allocation of non-renewable resources. Under the linear resource consumption function, the goal (version) is to determine the optimal sequence and optimal resource allocation such that the sum of scheduling cost and total resource consumption cost is minimized. Under the convex resource consumption function, three versions of the scheduling cost and total resource consumption cost are discussed. We prove that these four versions can be solved in polynomial time, respectively. Some applications are also given by using the scheduling cost, which involve the makespan, total completion time, total absolute differences in completion times (TADC), and total absolute differences in waiting times (TADW).
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-04-16T07:00:00Z
      DOI: 10.1142/S0217595921500135
       
  • A Proximal Bundle Method with Exact Penalty Technique and Bundle
           Modification Strategy for Nonconvex Nonsmooth Constrained Optimization

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      Authors: Xiaoliang Wang, Liping Pang, Qi Wu
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      The bundle modification strategy for the convex unconstrained problems was proposed by Alexey et al. [[2007] European Journal of Operation Research, 180(1), 38–47.] whose most interesting feature was the reduction of the calls for the quadratic programming solver. In this paper, we extend the bundle modification strategy to a class of nonconvex nonsmooth constraint problems. Concretely, we adopt the convexification technique to the objective function and constraint function, take the penalty strategy to transfer the modified model into an unconstrained optimization and focus on the unconstrained problem with proximal bundle method and the bundle modification strategies. The global convergence of the corresponding algorithm is proved. The primal numerical results show that the proposed algorithms are promising and effective.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-04-16T07:00:00Z
      DOI: 10.1142/S0217595921500159
       
  • An Online Scheduling Problem on a Drop-Line Parallel Batch Machine with
           Delivery Times and Limited Restart

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      Authors: Hailing Liu, Xiwen Lu
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      This paper studies online scheduling on an unbounded drop-line parallel batch machine with delivery times and limited restarts. A drop-line parallel batch machine is a system that can process some jobs simultaneously as a batch. Jobs in a batch have the same starting time and the completion time of a job is equal to its starting time plus its processing time. Limited restarts mean that a running batch containing at least one restarted job cannot be restarted again. The objective is to minimize the time by which all jobs have been delivered. We prove that any online algorithm has a competitive ratio of at least [math], where [math] is the positive solution of the equation [math]. We provide a best possible [math]-competitive online algorithm for the problem. Furthermore, we study the restricted problem with small delivery times and provide a best possible online algorithm with a competitive ratio of [math].
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-04-09T07:00:00Z
      DOI: 10.1142/S0217595921500111
       
  • An Integrated Response-Surface-Based Method for Simulation Optimization
           with Correlated Outputs

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      Authors: Kuo-Hao Chang, Hui-Yu Yang, Robert Cuckler
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      While nearly all previous algorithms designed to solve simulation optimization problems have treated the outputs of simulation systems at a given design point (input parameter) as being independent of each other, this premise is flawed in that simulated outputs are generally correlated. We propose a decorrelation (DC) procedure that can effectively evaluate and remove the correlation of outputs of a simulation system. The proposed DC procedure is further integrated with STRONG, an improved framework of the well-known Response Surface Methodology (RSM), for tackling the simulation optimization problems with correlated outputs. This integration is particularly synergistic due to the fact that STRONG is a fully automated, response-surface-based procedure possessing appealing convergence properties and DC can take advantage of the concept of trust region as in STRONG to enable the removal of the correlation of outputs at the design points within the same trust region all at once. This is more efficient compared to the traditional approaches where a substantial number of observations are typically required for dealing with correlations. The resulting integrated method, which we call STRONG-DC, requires various adaptations so as to ensure the efficacy and efficiency of the overall framework. STRONG-DC preserves the desirable automation and convergence as STRONG, namely, it does not require human involvements and can be proved to achieve the truly optimal solution(s) with probability one (w.p.1) under reasonable conditions. Moreover, the effectiveness and efficiency of STRONG-DC are evaluated through extensive numerical analyses, along with a case study involving the well-known newsvendor problem.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-04-09T07:00:00Z
      DOI: 10.1142/S0217595921500147
       
  • Error Bounds for Inverse Mixed Quasi-Variational Inequality via
           Generalized Residual Gap Functions

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      Authors: Yinfeng Zhang, Guolin Yu
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      In this paper, we investigate error bounds of an inverse mixed quasi variational inequality problem in Hilbert spaces. Under the assumptions of strong monotonicity of function couple, we obtain some results related to error bounds using generalized residual gap functions. Each presented error bound is an effective estimation of the distance between a feasible solution and the exact solution. Because the inverse mixed quasi-variational inequality covers several kinds of variational inequalities, such as quasi-variational inequality, inverse mixed variational inequality and inverse quasi-variational inequality, the results obtained in this paper can be viewed as an extension of the corresponding results in the related literature.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-04-09T07:00:00Z
      DOI: 10.1142/S0217595921500172
       
  • A Fast Algorithm for Knapsack Problem with Conflict Graph

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      Authors: Jiaxin Li, Yan Lan, Feng Chen, Xin Han, Jacek Blazewicz
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      In this paper, we propose a fast algorithm based on a new algorithm to calculate the upper bound for the knapsack problem with conflict graph (KPCG). The KPCG is an extension of the 0-1 knapsack problem. A pre-defined conflict graph defines the incompatibility properties between pairs of items. The goal is to determine which items should be packed into the knapsack to maximize the total profit on the premise of satisfying the capacity constraint and the incompatibility constraints. The experimental results show that for the graph with density greater than or equal to 0.1, the branch-and-bound algorithm based on the new algorithm is 1.6458 and 1.6352 times faster than the state-of-the-art algorithm on random and correlated instances, respectively, and can achieve speedups of up to 4.6477 for some low density instances. Moreover, the branch-and-bound algorithm based on the new algorithm can optimally solve more instances than the state-of-the-art algorithm in a given time limit.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-03-25T07:00:00Z
      DOI: 10.1142/S021759592150010X
       
  • A Time–Cost Tradeoff Problem with Multiple Assessments and Release Times
           on a Chain Precedence Graph

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      Authors: Myoung-Ju Park, Byung-Cheon Choi, Jibok Chung
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      We consider two variants of a time–cost tradeoff problem with multiple assessments on a chain precedence graph. Furthermore, each job can only be started after a release time, and a penalty cost is incurred when a job is not finished before its due date. The motivation is from the project such that a project owner can control the duration of each job and the support level of each project partner to avoid the penalty cost from the tardy jobs. We describe the penalty costs of the first and the second variants as the total weighted number of tardy jobs and the total weighted tardiness, respectively. These can be avoided by compressing the processing times or advancing the release times, which incurs a compression cost or release cost according to the linear and the piecewise constant functions, respectively. The objective is to minimize the total penalty, compression cost and release cost. In this paper, we propose the procedure based on the reduction to a shortest path problem, and show that the procedure can solve two variants in strongly polynomial time.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-03-25T07:00:00Z
      DOI: 10.1142/S0217595921500123
       
  • Real Options in a Duopoly with Jump Diffusion Prices

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      Authors: Wei Sun, Yonggan Zhao, Leonard MacLean
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      This paper analyzes irreversible investments in technology under asymmetric duopoly. Asset prices are defined by a diffusion with Poisson jumps. Assuming negative externalityfor profit flows, we develop a real options and game theoretic valuation model to evaluate the optimal investment strategies under interaction. Three types of equilibrium, i.e., simultaneous equilibrium, preemptive equilibrium, and sequential equilibrium, are attainable depending on the firms’ competitive advantageand first-mover advantage. The role of a firm, as “leader”, “follower”, or “simultaneous entrant”, is analyzed both exogenously and endogenously. We find that preemptive competition lowers both firms’ profits from the investments in the technology. Numerical examples illustrate the key results.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-03-22T07:00:00Z
      DOI: 10.1142/S0217595921500093
       
  • Study on Resource-Dependent No-Wait Flow Shop Scheduling with Different
           Due-Window Assignment and Learning Effects

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      Authors: Dan-Yang Lv, Ji-Bo Wang
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      In this paper, different due-window assignment flow shop scheduling problem with learning effect and resource allocation is considered. Under two machine no-wait flow shop setting, the goal is to determine the due-window starting time, due-window size, optimal resource allocation and the optimal sequence of all jobs. A bicriteria analysis of the problem is provided where the first criterion is to minimize the scheduling cost (including earliness-tardiness penalty, due-window starting time and due-window size of all jobs) and the second criterion is to minimize the resource consumption cost. It is shown that four versions about scheduling cost and resource consumption cost can be solved in polynomial time.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-03-15T07:00:00Z
      DOI: 10.1142/S0217595921500081
       
  • Strategic Manufacturers in Online Cash-Back Shopping

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      Authors: Chen Chen, Yongrui Duan
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Cash-back industry is now witnessing surging development. Prior works on cash-back sites focus mainly on the demand side, while we are also interested in the supply side. We develop a game theoretical model with a manufacturer, an online retailer, cash-back site(s), and heterogeneous consumers. We find that when the cash-back channel cannot attract new consumers, the manufacturer raises the wholesale price and the retailer raises the retail price, which may lead to the cash-back paradox where all consumers face higher prices. Therefore, when there exists a cash-back channel, the manufacturer is always worse off and the retailer is better off when low-type consumers’ product valuation is intermediate, and consumer surplus and social welfare are both lower. When the retailer affiliates with two competing cash-back sites, the manufacturer contributes to the mitigation of double marginalization problem by raising the wholesale price to a lesser extent, which drives the surprising result that when there exists downstream competition, cash-back sites enjoy higher commission rate and under some circumstances, offer lower cash-back rate and enjoy higher profit. We also show that only when the cash-back channel makes the size of the low-type segment double will the manufacturer be better off with this channel.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-03-13T08:00:00Z
      DOI: 10.1142/S0217595921500056
       
  • New Tests for Richness and Poorness: A Stochastic Dominance Analysis of
           Income Distributions in Hong Kong

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      Authors: Nikolai Sheung-Chi Chow, Maria Rebecca Valenzuela, Wing-Keung Wong
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      This paper applies stochastic dominance techniques for income distribution analysis and develops tests of richness and poorness to achieve more accurate characterizations of relative welfare in populations than was previously possible. Results from our empirical application, using Hong Kong data, are consistent with predictions of the life-cycle theory of income and savings. Among other things, we find high concentrations of poor individuals among the younger cohorts, and at the same time, there are high concentrations of rich individuals amongst the oldest cohorts. Our results help to explain Hong Kong’s persistently high levels of income inequality in the population.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-03-09T08:00:00Z
      DOI: 10.1142/S0217595920400254
       
  • An Alternative Approach to Dealing with the Composition Approach for
           Series Network Production Processes

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      Authors: Biresh K. Sahoo, Hilda Saleh, Morteza Shafiee, Kaoru Tone, Joe Zhu
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      To deal with efficiency assessment in a two-stage production process, Despotis et al. (2016b) proposed an innovative composition approach to calculate the two-stage efficiencies, whose minimum is defined as overall efficiency of the network production process. The underlying proposed programming method in this approach is nonlinear and requires the application of a very time-consuming bi-section procedure to obtain the stage efficiencies. In this paper, we have, therefore, proposed a simple linear network DEA model to carry out the same stage efficiency assessment, which is computationally efficient, and is also readily applicable to any multi-stage production process. Additionally, unlike the Despotis et al.’s (2016b) method, our proposed alternative is extended to deal with dynamic efficiency assessment. Finally, we have considered both synthetic and real-life data to demonstrate the ready applicability of our proposed models for both static and dynamic efficiency assessments.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-03-09T08:00:00Z
      DOI: 10.1142/S0217595921500044
       
  • Comparing Supply Chain Risks Ranking in Multi-Attribute Decision-Making
           Methods Using the Proposed Three-Dimensional Integration Mean Method

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      Authors: M. B. Fakhrzad, Mohammad Reza Firozpour, Hasan Hosseini Nasab
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Risks play an important role in supply chain vulnerability, performance maintenance, and competitive advantage. Therefore, appropriate risk assessment and ranking are among the top priorities of managers and experts in the supply chain. Because there are several quantitative and qualitative risks in the supply chain, multi-criteria decision-making (MCDM) and, in particular, multi attribute decision making (MADM) methods are used to rank them. Depending on the type of supply chain, the difference in criteria and information available, it is possible to use existing MCDM methods to rank supply chain risks or introduce new methods. In these methods, options are compared on the basis of different criteria according to mathematical methods. Each of these methods uses their own approaches and assumptions. Therefore, there will be different solutions to the ranking. In this case, one or more methods may be selected as the best method. But it cannot be sure that the superior method is chosen correctly. In this paper, decision making methods are compared with each other for an appropriate method to be chosen. Case examples from the related literature have been compared with the proposed method (three-dimensional integrated mean method). To evaluate the validity of the proposed method, the results were sent to experts in various industries along with the proposed method. For analysis the accuracy of experts’ opinions, One-Sample Kolmogorov-Smirnov, Frequencies and Explore tests have been used in SPSS software with 95% confidence level. The obtained results show high reliability of the proposed method for determining an appropriate decision-making method in supply chain risk assessment. However, the proposed method is used for ranking of supplier selection in this paper, but it can be used for many decision-making procedures.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-03-09T08:00:00Z
      DOI: 10.1142/S0217595921500068
       
  • A Parallel Machine Scheduling Problem Maximizing Total Weighted Early Work

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      Authors: Byung-Cheon Choi, Myoung-Ju Park, Kyung Min Kim, Yunhong Min
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      We consider the total weighted early work maximization problem on identical machines in parallel such that the weights are identical, or the due date is the same. First, we present an approach to solve the case with a fixed number of machines in pseudo-polynomial time. Then, we develop approximation algorithms for the two cases with identical weights and with a common due date. For the case with identical weights, furthermore, we show that the parallel-machine and a single-machine cases are strongly NP-hard and weakly NP-hard, respectively, even if the due date of each job is equal to the processing time multiplied by a constant.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-03-09T08:00:00Z
      DOI: 10.1142/S021759592150007X
       
  • The Benefits of Diversification Between Bitcoin, Bonds, Equities and the
           US Dollar: A Matter of Portfolio Construction

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      Authors: Abdulnasser Hatemi-J, Mohamed A. Hajji, Elie Bouri, Rangan Gupta
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      This paper investigates the potential portfolio diversification between Bitcoin, bonds, equities, and the US dollar. We make use of two approaches for constructing the portfolio. The first is the standard minimum variance approach, and the alternative is based on combining risk and return when the portfolio is constructed. The portfolio based on the minimum variance approach does not result in increasing the return per unit of risk compared to the corresponding value for the best single asset, in this case, Bitcoin. However, the portfolio based on the approach that combines risk and return in the optimization problem does show a return per unit risk higher than the corresponding value for any of the four assets. Thus, the portfolio diversification benefit with respect to these four assets, in terms of return per unit risk, exists only if the portfolio is constructed via the new approach.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-02-27T08:00:00Z
      DOI: 10.1142/S0217595920400242
       
  • A Risk Measurement Model of China’s Non-Ferrous Metal Futures Market

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      Authors: Hong Shen, Jinling Zhang, Xu Li, Pin T. Ng
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      With the impact of foreign exchange markets, risks in financial markets are becoming more complex and diversified, which underlines the importance of risk management in financial supervision. In this paper, China’s non-ferrous metal futures market is selected as the research object, and Shanghai Futures Exchange’s Industrial Metal Commodity Index (IMCI) data are used to measure risk using the conditional autoregressive value at risk (CAViaR) model. The US dollar index (USDX) is incorporated into the CAViaR model to study its impact on the risk. Through empirical analysis, we arrive at the following conclusions: First, the asymmetric slope CAViaR model (AS-CAViaR) is more suitable for measuring the risk in China’s non-ferrous metal futures market. Second, the risk is positively impacted by the lagged risk. Moreover, the impacts of positive and negative returns on the risk are asymmetric, with a negative return having a greater impact. Third, the positive and negative shock of USDX has significant and different impacts on the risk. These impacts can be caused by global capital flows. In addition, the impact of the vector of explanatory variables on the IMCI at different quantile levels is discussed based on the CAViaR-USDX model, which reflects the comprehensive advantages of the quantile regression method and the model’s applicability. The above conclusions verify the impact of USDX on China’s non-ferrous metal futures market and provide a theoretical basis and direction for risk monitoring.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-02-27T08:00:00Z
      DOI: 10.1142/S0217595920400266
       
  • The Impact of Government Subsidies and Retailer Contracts on Product
           Recovery

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      Authors: Pan Zhang, Chien-Chiang Lee, Yongqi Wu
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Conducting product recovery and remanufacturing not only help manufacturers decrease the unit cost of production, but also benefit the environment. However, most manufacturers are hampered by the huge initial investment of related operations. In order to alleviate the manufacturers’ financial pressure of product recovery and remanufacturing, some governments implement the production subsidy (subsidy [math]) and recycling subsidy (subsidy [math]). Meanwhile, retailers can provide the revenue-sharing contract (contract [math]) and cost-sharing contract (contract [math]). Hence, this paper mainly studies the incentive designs of the government and retailer, and the effects of these incentives on the closed-loop supply chain. We first establish a Stackelberg game model consisting of a government, a manufacturer and a retailer, then investigate and compare the optimal decisions and payoffs of each member under each incentive combination of the government and retailer. Our results first show that, on the other hand, the government’s subsidy type cannot affect the retailer’s design of contract [math], but subsidy [math] can induce the retailer to share a higher rate of sale revenue, comparing to subsidy [math]. On the other hand, the retailer’s contract [math] could induce the government to increase subsidy rate in most cases, comparing to contract [math]. Second, the subsidy [math] can always lead to a higher collection rate, lower wholesale and retail prices, and higher payoffs for the government, manufacturer and retailer, comparing to subsidy [math]. Besides, under subsidy [math], contract [math] always leads to a higher collection rate, lower wholesale and retail prices, and higher payoffs for the government, manufacturer and retailer, comparing to contract [math]. However, under subsidy [math], contract [math] can lead to a higher collection rate, a lower wholesale price, and higher payoffs for the manufacturer and retailer, comparing to contract [math] only when the manufacturer’s recovery efficiency is high. Moreover, the retail price is always higher and the government payoffs is always lower under contract [math]. Third, the government prefers to implement the subsidy [math] and then which contract is chosen by the retailer depends on the collection efficiency of the manufacturer. Therefore, subsidy [math] combining with contract [math] or [math] is the equilibrium incentive combination.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-02-25T08:00:00Z
      DOI: 10.1142/S0217595920400230
       
  • Operational Research for Technology-Driven Supply Chains in the Industry
           4.0 Era: Recent Development and Future Studies

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      Authors: Suyuan Luo, Tsan-Ming Choi
      Abstract: Asia-Pacific Journal of Operational Research, Ahead of Print.
      Today, supply chain operations have entered the Industry 4.0 era. Technologies, such as blockchain, big-data, artificial intelligence, additive manufacturing and cloud-computing, are all hot topics. Motivated by their importance, in this paper, we conduct a review of the closely related literature in the well-established mainstream operational research (OR) journals. From our research, we first examine the OR literature on Industry 4.0 related studies. Then we classify the technology-operations-related literature into three major categories, namely, information technologies for supply chain operations, technologies for sustainable operations, and technologies for production operations. Various less popular areas on technology-driven operations in supply chains, namely, technology licensing and outsourcing (TLO), online data, and risk, finance and security (RFS), are also examined. From the reviews, we identify the major research gaps. After that, we establish a future research agenda. We believed that this paper lays the foundation for further OR studies on technology-driven supply chain management in the Industry 4.0 era.
      Citation: Asia-Pacific Journal of Operational Research
      PubDate: 2021-02-23T08:00:00Z
      DOI: 10.1142/S0217595920400217
       
 
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