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  Subjects -> BUSINESS AND ECONOMICS (Total: 3126 journals)
    - ACCOUNTING (93 journals)
    - BANKING AND FINANCE (268 journals)
    - BUSINESS AND ECONOMICS (1157 journals)
    - CONSUMER EDUCATION AND PROTECTION (23 journals)
    - COOPERATIVES (4 journals)
    - ECONOMIC SCIENCES: GENERAL (166 journals)
    - ECONOMIC SYSTEMS, THEORIES AND HISTORY (180 journals)
    - FASHION AND CONSUMER TRENDS (13 journals)
    - HUMAN RESOURCES (93 journals)
    - INSURANCE (23 journals)
    - INTERNATIONAL COMMERCE (125 journals)
    - INTERNATIONAL DEVELOPMENT AND AID (83 journals)
    - INVESTMENTS (27 journals)
    - LABOR AND INDUSTRIAL RELATIONS (43 journals)
    - MACROECONOMICS (15 journals)
    - MANAGEMENT (525 journals)
    - MARKETING AND PURCHASING (89 journals)
    - MICROECONOMICS (24 journals)
    - PRODUCTION OF GOODS AND SERVICES (138 journals)
    - PUBLIC FINANCE, TAXATION (35 journals)
    - TRADE AND INDUSTRIAL DIRECTORIES (2 journals)

BUSINESS AND ECONOMICS (1157 journals)                  1 2 3 4 5 6 | Last

Showing 1 - 200 of 1566 Journals sorted alphabetically
4OR: A Quarterly Journal of Operations Research     Hybrid Journal   (Followers: 9)
Abacus     Hybrid Journal   (Followers: 12)
Accounting Forum     Hybrid Journal   (Followers: 25)
Acta Amazonica     Open Access   (Followers: 4)
Acta Commercii     Open Access   (Followers: 3)
Acta Oeconomica     Full-text available via subscription   (Followers: 2)
Acta Scientiarum. Human and Social Sciences     Open Access   (Followers: 5)
Acta Universitatis Danubius. Œconomica     Open Access   (Followers: 2)
Acta Universitatis Nicolai Copernici Zarządzanie     Open Access   (Followers: 3)
AD-minister     Open Access   (Followers: 2)
ADR Bulletin     Open Access   (Followers: 5)
Advances in Developing Human Resources     Hybrid Journal   (Followers: 21)
Advances in Economics and Business     Open Access   (Followers: 11)
AfricaGrowth Agenda     Full-text available via subscription   (Followers: 1)
African Affairs     Hybrid Journal   (Followers: 59)
African Development Review     Hybrid Journal   (Followers: 34)
African Journal of Business and Economic Research     Full-text available via subscription   (Followers: 1)
African Journal of Business Ethics     Open Access   (Followers: 6)
African Review of Economics and Finance     Open Access   (Followers: 3)
Afro-Asian Journal of Finance and Accounting     Hybrid Journal   (Followers: 7)
Afyon Kocatepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi     Open Access   (Followers: 3)
Agronomy     Open Access   (Followers: 11)
Akademika : Journal of Southeast Asia Social Sciences and Humanities     Open Access   (Followers: 4)
Alphanumeric Journal : The Journal of Operations Research, Statistics, Econometrics and Management Information Systems     Open Access   (Followers: 4)
American Economic Journal : Applied Economics     Full-text available via subscription   (Followers: 150)
American Journal of Business     Hybrid Journal   (Followers: 15)
American Journal of Business and Management     Open Access   (Followers: 53)
American Journal of Business Education     Open Access   (Followers: 10)
American Journal of Economics and Business Administration     Open Access   (Followers: 26)
American Journal of Economics and Sociology     Hybrid Journal   (Followers: 28)
American Journal of Evaluation     Hybrid Journal   (Followers: 13)
American Journal of Finance and Accounting     Hybrid Journal   (Followers: 19)
American Journal of Health Economics     Full-text available via subscription   (Followers: 12)
American Journal of Industrial and Business Management     Open Access   (Followers: 23)
American Journal of Medical Quality     Hybrid Journal   (Followers: 7)
American Law and Economics Review     Hybrid Journal   (Followers: 25)
ANALES de la Universidad Central del Ecuador     Open Access   (Followers: 2)
Annales de l'Institut Henri Poincare (C) Non Linear Analysis     Full-text available via subscription   (Followers: 1)
Annals in Social Responsibility     Full-text available via subscription  
Annals of Finance     Hybrid Journal   (Followers: 28)
Annals of Operations Research     Hybrid Journal   (Followers: 8)
Annual Review of Economics     Full-text available via subscription   (Followers: 30)
Applied Developmental Science     Hybrid Journal   (Followers: 3)
Applied Economics     Hybrid Journal   (Followers: 48)
Applied Economics Letters     Hybrid Journal   (Followers: 29)
Applied Economics Quarterly     Full-text available via subscription   (Followers: 10)
Applied Financial Economics     Hybrid Journal   (Followers: 23)
Applied Mathematical Finance     Hybrid Journal   (Followers: 7)
Applied Stochastic Models in Business and Industry     Hybrid Journal   (Followers: 5)
Arab Economic and Business Journal     Open Access   (Followers: 3)
Archives of Business Research     Open Access   (Followers: 5)
Arena Journal     Full-text available via subscription   (Followers: 1)
Argomenti. Rivista di economia, cultura e ricerca sociale     Open Access   (Followers: 2)
ASEAN Economic Bulletin     Full-text available via subscription   (Followers: 5)
Asia Pacific Business Review     Hybrid Journal   (Followers: 5)
Asia Pacific Journal of Human Resources     Hybrid Journal   (Followers: 313)
Asia Pacific Viewpoint     Hybrid Journal   (Followers: 1)
Asia-Pacific Journal of Business Administration     Hybrid Journal   (Followers: 3)
Asia-Pacific Journal of Operational Research     Hybrid Journal   (Followers: 3)
Asia-Pacific Management and Business Application     Open Access  
Asian Business Review     Open Access   (Followers: 2)
Asian Case Research Journal     Hybrid Journal   (Followers: 1)
Asian Development Review     Open Access   (Followers: 14)
Asian Economic Journal     Hybrid Journal   (Followers: 8)
Asian Economic Papers     Hybrid Journal   (Followers: 7)
Asian Economic Policy Review     Hybrid Journal   (Followers: 4)
Asian Journal of Accounting and Governance     Open Access   (Followers: 4)
Asian Journal of Business Ethics     Hybrid Journal   (Followers: 7)
Asian Journal of Social Sciences and Management Studies     Open Access   (Followers: 7)
Asian Journal of Sustainability and Social Responsibility     Open Access   (Followers: 1)
Asian Journal of Technology Innovation     Hybrid Journal   (Followers: 8)
Asian-pacific Economic Literature     Hybrid Journal   (Followers: 5)
AStA Wirtschafts- und Sozialstatistisches Archiv     Hybrid Journal   (Followers: 5)
Atlantic Economic Journal     Hybrid Journal   (Followers: 15)
Australasian Journal of Regional Studies, The     Full-text available via subscription   (Followers: 2)
Australian Cottongrower, The     Full-text available via subscription   (Followers: 1)
Australian Economic Papers     Hybrid Journal   (Followers: 29)
Australian Economic Review     Hybrid Journal   (Followers: 6)
Australian Journal of Maritime and Ocean Affairs     Hybrid Journal   (Followers: 10)
Balkan Region Conference on Engineering and Business Education     Open Access   (Followers: 1)
Baltic Journal of Real Estate Economics and Construction Management     Open Access   (Followers: 1)
Banks in Insurance Report     Hybrid Journal   (Followers: 1)
BBR - Brazilian Business Review     Open Access   (Followers: 4)
Benchmarking : An International Journal     Hybrid Journal   (Followers: 11)
Benefit : Jurnal Manajemen dan Bisnis     Open Access  
BER : Consumer Confidence Survey     Full-text available via subscription   (Followers: 4)
BER : Economic Prospects : An Executive Summary     Full-text available via subscription  
BER : Economic Prospects : Full Survey     Full-text available via subscription   (Followers: 2)
BER : Intermediate Goods Industries Survey     Full-text available via subscription   (Followers: 1)
BER : Manufacturing Survey : Full Survey     Full-text available via subscription   (Followers: 2)
BER : Motor Trade Survey     Full-text available via subscription   (Followers: 1)
BER : Retail Sector Survey     Full-text available via subscription   (Followers: 2)
BER : Retail Survey : Full Survey     Full-text available via subscription   (Followers: 2)
BER : Survey of Business Conditions in Building and Construction : An Executive Summary     Full-text available via subscription   (Followers: 4)
BER : Survey of Business Conditions in Manufacturing : An Executive Summary     Full-text available via subscription   (Followers: 3)
BER : Survey of Business Conditions in Retail : An Executive Summary     Full-text available via subscription   (Followers: 3)
BER : Trends : Full Survey     Full-text available via subscription   (Followers: 2)
BER : Wholesale Sector Survey     Full-text available via subscription   (Followers: 1)
Berkeley Business Law Journal     Free   (Followers: 10)
Bio-based and Applied Economics     Open Access   (Followers: 1)
Biodegradation     Hybrid Journal   (Followers: 1)
Biology Direct     Open Access   (Followers: 7)
Black Enterprise     Full-text available via subscription  
Board & Administrator for Administrators only     Hybrid Journal  
Border Crossing : Transnational Working Papers     Open Access   (Followers: 2)
Briefings in Real Estate Finance     Hybrid Journal   (Followers: 5)
British Journal of Industrial Relations     Hybrid Journal   (Followers: 35)
Brookings Papers on Economic Activity     Open Access   (Followers: 48)
Brookings Trade Forum     Full-text available via subscription   (Followers: 3)
BRQ Business Research Quarterly     Open Access   (Followers: 2)
Building Sustainable Legacies : The New Frontier Of Societal Value Co-Creation     Full-text available via subscription   (Followers: 1)
Bulletin of Economic Research     Hybrid Journal   (Followers: 17)
Bulletin of Geography. Socio-economic Series     Open Access   (Followers: 7)
Bulletin of Indonesian Economic Studies     Hybrid Journal   (Followers: 3)
Bulletin of the Dnipropetrovsk University. Series : Management of Innovations     Open Access   (Followers: 1)
Business & Entrepreneurship Journal     Open Access   (Followers: 18)
Business & Information Systems Engineering     Hybrid Journal   (Followers: 5)
Business & Society     Hybrid Journal   (Followers: 9)
Business : Theory and Practice / Verslas : Teorija ir Praktika     Open Access   (Followers: 1)
Business and Economic Research     Open Access   (Followers: 6)
Business and Management Horizons     Open Access   (Followers: 12)
Business and Management Research     Open Access   (Followers: 17)
Business and Management Studies     Open Access   (Followers: 9)
Business and Politics     Hybrid Journal   (Followers: 6)
Business and Professional Communication Quarterly     Hybrid Journal   (Followers: 7)
Business and Society Review     Hybrid Journal   (Followers: 5)
Business Economics     Hybrid Journal   (Followers: 6)
Business Ethics: A European Review     Hybrid Journal   (Followers: 16)
Business Horizons     Hybrid Journal   (Followers: 9)
Business Information Review     Hybrid Journal   (Followers: 14)
Business Management and Strategy     Open Access   (Followers: 43)
Business Research     Hybrid Journal   (Followers: 2)
Business Strategy and the Environment     Hybrid Journal   (Followers: 13)
Business Strategy Review     Hybrid Journal   (Followers: 7)
Business Strategy Series     Hybrid Journal   (Followers: 6)
Business Systems & Economics     Open Access   (Followers: 2)
Business Systems Research Journal     Open Access   (Followers: 5)
Business, Management and Education     Open Access   (Followers: 18)
Business, Peace and Sustainable Development     Full-text available via subscription   (Followers: 3)
Bustan     Hybrid Journal   (Followers: 1)
Cadernos EBAPE.BR     Open Access   (Followers: 1)
Cambridge Journal of Economics     Hybrid Journal   (Followers: 58)
Cambridge Journal of Regions, Economy and Society     Hybrid Journal   (Followers: 11)
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: 28)
Canadian journal of nonprofit and social economy research     Open Access   (Followers: 2)
Capitalism and Society     Hybrid Journal   (Followers: 2)
Capitalism Nature Socialism     Hybrid Journal   (Followers: 12)
Case Studies in Business and Management     Open Access   (Followers: 9)
CBU International Conference Proceedings     Open Access   (Followers: 1)
Central European Business Review     Open Access   (Followers: 1)
Central European Journal of Operations Research     Hybrid Journal   (Followers: 5)
Central European Journal of Public Policy     Open Access   (Followers: 2)
CESifo Economic Studies     Hybrid Journal   (Followers: 16)
Chain Reaction     Full-text available via subscription  
Challenge     Full-text available via subscription   (Followers: 4)
China & World Economy     Hybrid Journal   (Followers: 15)
China : An International Journal     Full-text available via subscription   (Followers: 16)
China Economic Journal: The Official Journal of the China Center for Economic Research (CCER) at Peking University     Hybrid Journal   (Followers: 10)
China Economic Review     Hybrid Journal   (Followers: 9)
China Finance Review International     Hybrid Journal   (Followers: 5)
China Nonprofit Review     Hybrid Journal   (Followers: 3)
China perspectives     Open Access   (Followers: 11)
Chinese Economy     Full-text available via subscription  
Ciência & Saúde Coletiva     Open Access   (Followers: 2)
CLIO América     Open Access   (Followers: 1)
Cliometrica     Hybrid Journal   (Followers: 3)
COEPTUM     Open Access  
Community Development Journal     Hybrid Journal   (Followers: 24)
Compensation & Benefits Review     Hybrid Journal   (Followers: 7)
Competition & Change     Hybrid Journal   (Followers: 10)
Competitive Intelligence Review     Hybrid Journal   (Followers: 2)
Competitiveness Review : An International Business Journal incorporating Journal of Global Competitiveness     Hybrid Journal   (Followers: 6)
Computational Economics     Hybrid Journal   (Followers: 9)
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 8)
Computer Law & Security Review     Hybrid Journal   (Followers: 16)
Computers & Operations Research     Hybrid Journal   (Followers: 10)
Construction Innovation: Information, Process, Management     Hybrid Journal   (Followers: 14)
Contemporary Wales     Full-text available via subscription   (Followers: 3)
Contextus - Revista Contemporânea de Economia e Gestão     Open Access   (Followers: 1)
Contributions to Political Economy     Hybrid Journal   (Followers: 5)
Corporate Communications An International Journal     Hybrid Journal   (Followers: 6)
Corporate Philanthropy Report     Hybrid Journal   (Followers: 2)
Corporate Reputation Review     Hybrid Journal   (Followers: 4)
Creative and Knowledge Society     Open Access   (Followers: 10)
Creative Industries Journal     Hybrid Journal   (Followers: 9)
CRIS - Bulletin of the Centre for Research and Interdisciplinary Study     Open Access   (Followers: 1)
Crossing the Border : International Journal of Interdisciplinary Studies     Open Access   (Followers: 4)
Cuadernos de Administración (Universidad del Valle)     Open Access   (Followers: 2)
Cuadernos de Economía     Open Access   (Followers: 2)
Cuadernos de Economia - Latin American Journal of Economics     Open Access   (Followers: 2)
Cuadernos de Estudios Empresariales     Open Access   (Followers: 2)
Current Opinion in Creativity, Innovation and Entrepreneurship     Open Access   (Followers: 9)
De Economist     Hybrid Journal   (Followers: 12)
Decision Analysis     Full-text available via subscription   (Followers: 8)
Decision Sciences     Hybrid Journal   (Followers: 16)
Decision Support Systems     Hybrid Journal   (Followers: 16)
Defence and Peace Economics     Hybrid Journal   (Followers: 17)
der markt     Hybrid Journal   (Followers: 1)
Desenvolvimento em Questão     Open Access  

        1 2 3 4 5 6 | Last

Journal Cover Computers & Operations Research
  [SJR: 2.237]   [H-I: 104]   [10 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0305-0548
   Published by Elsevier Homepage  [3043 journals]
  • Hybrid genetic algorithm for the open capacitated arc routing problem
    • Abstract: Publication date: February 2018
      Source:Computers & Operations Research, Volume 90
      Author(s): Rafael Kendy Arakaki, Fábio Luiz Usberti
      The Open Capacitated Arc Routing Problem (OCARP) is an NP-hard arc routing problem where, given an undirected graph, the objective is to find the least cost set of routes that services all edges with positive demand (required edges). The routes are subjected to capacity constraints in relation to edge demands. The OCARP differs from the Capacitated Arc Routing Problem (CARP) since OCARP does not consider a depot and routes are not constrained to form cycles. A hybrid genetic algorithm with feasibilization and local search procedures is proposed for the OCARP. Computational experiments conducted on a set of benchmark instances reveal that the proposed hybrid genetic algorithm achieved the best upper bounds for almost all instances.

      PubDate: 2017-10-11T07:09:30Z
       
  • Sustainable operations modeling and data analytics
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Angappa Gunasekaran, Nachiappan Subramanian
      This editorial introduces the unique attributes of this special issue in the era of climate change, modern slavery, and big data. This special issue envisages the depth of penetration of sustainability, from strategy to the operations level, to understand the extent to which sustainability has attracted researchers and practitioners in dealing with various facets of operations management. Overall, it is encouraging to notice the research developments in all facets of operations management except process type, layout type, forecasting, and queuing. Out of three sustainability dimensions, this special issue received substantial contributions on economic and environmental aspects. All the contributions had at least two sustainability components in their decision models as well as newer analytical solutions. At the end, this piece outlines future research challenges and potential research opportunities.

      PubDate: 2017-10-11T07:09:30Z
       
  • Modeling a green inventory routing problem for perishable products with
           horizontal collaboration
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Mehmet Soysal, Jacqueline M. Bloemhof-Ruwaard, Rene Haijema, Jack G.A.J. van der Vorst
      Increasing concerns on energy use, emissions and food waste requires advanced models for food logistics management. Our interest in this study is to analyse the benefits of horizontal collaboration related to perishability, energy use (CO2 emissions) from transportation operations and logistics costs in the Inventory Routing Problem (IRP) with multiple suppliers and customers by developing a decision support model that can address these concerns. The proposed model allows us to analyse the benefits of horizontal collaboration in the IRP with respect to several Key Performance Indicators, i.e., emissions, driving time, total cost comprised of routing (fuel and wage cost), inventory and waste cost given an uncertain demand. A case study on the distribution operations of two suppliers, where the first supplier produces figs and the second supplier produces cherries, shows the applicability of the model to a real-life problem. The results show that horizontal collaboration among the suppliers contributes to the decrease of aggregated total cost and emissions in the logistics system. The obtained gains are sensitive to the changes in parameters such as supplier size or maximum product shelf life. According to experiments, the aggregated total cost benefit from cooperation varies in a range of about 4–24% and the aggregated total emission benefit varies in a range of about 8–33% compared to the case where horizontal collaboration does not exist.

      PubDate: 2017-10-11T07:09:30Z
       
  • Mathematical models for green vehicle routing problems with pickup and
           delivery: A case of semiconductor supply chain
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Sakthivel Madankumar, Chandrasekharan Rajendran
      In this paper, we consider a special case of vehicle routing problem that addresses the routing problem in a semiconductor supply chain. This paper proposes two Mixed Integer Linear Programming (MILP) models for solving the Green Vehicle Routing Problems with Pickups and Deliveries in a Semiconductor Supply Chain (G-VRPPD-SSC). The first MILP model considers the basic G-VRPPD-SSC problem, and the objective is to find the set of minimum cost routes and schedules for the alternative fuel vehicles in order to satisfy a set of requests which comprise pickup and delivery operations, without violating the product and vehicle compatibility, vehicle capacity, request-priorities and request-types, and start/completion time constraints. The second model extends the first model in order to handle the scenario of having different fuel prices at different refueling stations, and the objective is to minimize the sum of costs of operating alternative fuel vehicles, which include both the routing cost and the refueling cost. To relatively evaluate the performance of the proposed MILP models, we consider the Pickup and Delivery Problem in a Semiconductor Supply Chain (PDP-SSC) without the presence of alternative fuel vehicles, and we present the corresponding MILP model. Our model is compared with an MILP model present in the literature. Our study indicates that the proposed model for the PDP-SSC gives better lower bounds than that by the existing work, apart from performing better than the existing work in terms of requiring less CPU time. In all cases, the proposed three MILP models preform quite good in terms of the execution time to solve the generated problem instances.

      PubDate: 2017-10-11T07:09:30Z
       
  • Optimisation of transportation service network using κ-node large
           neighbourhood search
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Ruibin Bai, John R. Woodward, Nachiappan Subramanian, John Cartlidge
      The Service Network Design Problem (SNDP) is generally considered as a fundamental problem in transportation logistics and involves the determination of an efficient transportation network and corresponding schedules. The problem is extremely challenging due to the complexity of the constraints and the scale of real-world applications. Therefore, efficient solution methods for this problem are one of the most important research issues in this field. However, current research has mainly focused on various sophisticated high-level search strategies in the form of different local search metaheuristics and their hybrids. Little attention has been paid to novel neighbourhood structures which also play a crucial role in the performance of the algorithm. In this research, we propose a new efficient neighbourhood structure that uses the SNDP constraints to its advantage and more importantly appears to have better reachability than the current ones. The effectiveness of this new neighbourhood is evaluated in a basic Tabu Search (TS) metaheuristic and a basic Guided Local Search (GLS) method. Experimental results based on a set of well-known benchmark instances show that the new neighbourhood performs better than the previous arc-flipping neighbourhood. The performance of the TS metaheuristic based on the proposed neighbourhood is further enhanced through fast neighbourhood search heuristics and hybridisation with other approaches.

      PubDate: 2017-10-11T07:09:30Z
       
  • The inventory centralization impacts on sustainability of the blood supply
           chain
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Zahra Hosseinifard, Babak Abbasi
      This paper studies the significance of inventory centralization at the second echelon of a two-echelon supply chain with perishable items when the agents of the second echelon use an ( S − 1 , S ) inventory policy. The replenishment at the first echelon is considered to be stochastic. The context in which the studied problem exists is in the blood supply network where the first echelon includes a single blood bank that receives stochastic supply from donors. The second echelon contains hospitals receiving external demands (transfusions). In our proposed structure, some of the hospitals in close proximity of each other maintain centralized inventories to serve their demands in addition to the demands by other neighbour hospitals. The results demonstrate that centralization of hospitals’ inventory is a key factor in the blood supply chain and can increase the sustainability and resilient of the blood supply chain. Using numerical study, it was observed that reducing the number of hospitals that hold inventory from 7 to 3 decreases outdate and shortage in the supply chain by 21% and 40% respectively.

      PubDate: 2017-10-11T07:09:30Z
       
  • Sustainable decision model for liner shipping industry
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Calwin S. Parthibaraj, Nachiappan Subramanian, P.L.K. Palaniappan, Kee-hung Lai
      Maritime transport facilitates international trade activities and contributes to world׳s economic growth and prosperity. Still maritime transport faces several operations challenges such as non-storability of shipping space, matching supply with dynamic shipping demand, and non-availability of fair allocation mechanism in the age of information exchange systems due to ban of anticompetitive liner conference amongst others. This paper develops a sustainable decision model for allocating ship capacity to satisfy shipping demand and to generate a route plan. The model is referred as sustainable because it determines flexible freight rates and coordinates market players with social interest. The paper uses multi-agent system modeling and an iterative combinatorial auction mechanism with Vickrey–Clarke–Groves payments to deploy ships at economically efficient prices in the age of information exchange systems. To tackle the computational complexity of multi-agent system model with auction mechanism, this paper proposes an enumerative search algorithm. Our proposed model and method can aid liner shipping industry managers to better realize their desired economical and social sustainable decisions targets by sharing information, costs, and benefits.

      PubDate: 2017-10-11T07:09:30Z
       
  • Optimal operation policy for a sustainable recirculation aquaculture
           system for ornamental fish: Simulation and response surface methodology
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Hadas Elalouf, Moshe Kaspi, Amir Elalouf, Ilan Halachmi
      Recirculating aquaculture systems (RAS) require a large investment in construction, equipment and energy. To ensure sufficient return on these investments, RAS operations must be managed meticulously. RAS managers must consider numerous factors related to the biological traits of the fish, logistics, seasonal market demand, and livestock management. RAS that specialize in ornamental fish are faced with particular challenges in that a given species of fish may actually yield several different "products," distinguished, for example, by color, which can be sold at different sizes for different prices. RAS managers need to consider the market prices of different-sized fish in the light of their production costs (cost of food and space, dependent on time in the system). The current study aims to develop an optimization model for the operations management of RAS specializing in ornamental fish. The objective of the model is to maximize annual profit. The methods used include: a general simulation model, built in Arena 11.0®, that seeks to mimic the studied system; an optimization procedure based on response surface methodology (RSM), including design of simulation experiments, stepwise regression (in SPSS® 11.0), and a nonlinear objective function and constraints solved with MATLAB®. The method is demonstrated in a case study—a RAS on Kibbutz Hazorea, Israel, raising ornamental koi fish (Cyprinus carpio).

      PubDate: 2017-10-11T07:09:30Z
       
  • Planning of complex supply chains: A performance comparison of three
           meta-heuristic algorithms
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Behnam Fahimnia, Hoda Davarzani, Ali Eshragh
      Businesses have more complex supply chains than ever before. Many supply chain planning efforts result in sizable and often nonlinear optimization problems that are difficult to solve using standard solution methods. Meta-heuristic and heuristic solution methods have been developed and applied to tackle such modeling complexities. This paper aims to compare and analyze the performance of three meta-heuristic algorithms in solving a nonlinear green supply chain planning problem. A tactical planning model is presented that aims to balance the economic and emissions performance of the supply chain. Utilizing data from an Australian clothing manufacturer, three meta-heuristic algorithms including Genetic Algorithm, Simulated Annealing and Cross-Entropy are adopted to find solutions to this problem. Discussions on the key characteristics of these algorithms and comparative analysis of the numerical results provide some modeling insights and practical implications. In particular, we find that (1) a Cross-Entropy method outperforms the two popular meta-heuristic algorithms in both computation time and solution quality, and (2) Simulated Annealing may produce better results in a time-restricted comparison due to its rapid initial convergence speed.

      PubDate: 2017-10-11T07:09:30Z
       
  • Remanufacturing with trade-ins under carbon regulations
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Zhaowei Miao, Huiqiang Mao, Ke Fu, Yu Wang
      Observing prevalent concerns about the influence of carbon emissions on climate change, we address the problem of remanufacturing with trade-ins under carbon regulations. We analyze the optimal pricing and production decisions of the manufacturer under the carbon tax policy and the cap and trade program. The results show that the introduction of carbon regulations can promote sales of remanufactured products while reducing the demands of new products. However, the implementation of carbon regulations has negative impacts on the manufacturer's profits. Nevertheless, the manufacturer's profits can be improved through deliberately designed government subsidy schemes. We also demonstrate that the government has the incentive to propose such subsidy schemes because the total emissions can be reduced under well-designed regulations, but not at the cost of the manufacturer's profits.

      PubDate: 2017-10-11T07:09:30Z
       
  • An integrated approach to evaluating sustainability in supply chains using
           evolutionary game theory
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Sujatha Babu, Usha Mohan
      Sustainability in supply chains is typically studied across one or more dimensions such as environmental, social, economic, culture and governance. Traditionally sustainability in supply chains has focused on environmental dimensions, while a few have attempted to focus on social and economic dimensions without really integrating them. There has been only a small effort to define sustainability by integrating all relevant dimensions (a holistic approach). This paper proposes to fill this gap. We identify sustainability of a supply chain with the equilibrium of the system over a long (but finite) period of time after integrating the various dimensions. Thus it necessitates looking at factors that can cause a shift in the equilibrium. Towards this, we propose to build a strong theoretical framework to integrate, explain, and predict sustainability for supply chains using cross-disciplinary effort. In our theoretical framework, evolutionary game theory serves as the pure conceptual theory-building tool, the metrics are qualitative in nature and the indicators are quantitative statistical measures. The use of evolutionary game theory concepts allows us to understand how sometimes trivial actions by members of the supply chain can trigger cascading effects that can move the system away from equilibrium. One of the salient aspects of our model is its complete scalability in terms of changes to the dimensions and metrics. As an example, we explain and predict social and economic sustainability (in tandem) for a public health insurance supply chain using evolutionary game theory.

      PubDate: 2017-10-11T07:09:30Z
       
  • Can lean lead to green' Assessment of radial tyre manufacturing
           processes using system dynamics modelling
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Vipul Gupta, Gopalakrishnan Narayanamurthy, Padmanav Acharya
      Even though tyre sector within rubber industry has been recognised to be the major contributor towards environmental pollution, hardly any study has been done to assess the processes involved and its associated wastes to reduce the detrimental impact on the environment. In addition, with the challenges and competitions existing in Indian manufacturing system, domestic tyre manufacturers are struggling for their competitive sustenance. This situation is particularly severe in the radial tyre manufacturing unit, which involves very complex manufacturing process, thereby increasing the volume of wasteful activities. Therefore, tyre manufacturing units are struggling for both their economic and environmental sustainability. Using the well accepted lean manufacturing principles, this paper investigates the processes and the associated wastes of radial tyre manufacturing. The paper presents a novel approach for assessing the wastes using a system dynamics model and validates the model in a radial tyre manufacturing case organisation in India. Scenario analysis by varying the level of employee skills, manpower availability, and machine availability is conducted. The model in addition to showing the overall performance of the radial tyre manufacturing unit assessed, throws light on the amount of greenness attainable by the organisation through the implementation of lean thinking. Wastes which had a substantial impact and subordinate impact on improving the lean and green performance are identified. The study is unique in studying the highly polluting sector which has received the least attention in both OM researcher's and practitioner's literature. The study is also novel in adopting system dynamics modelling to answer the research questions raised and provide implications for theory and practice.

      PubDate: 2017-10-11T07:09:30Z
       
  • A global optimization for sustainable multi-domain global manufacturing
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Yohanes Kristianto, Angappa Gunasekaran
      A multi-period and domain nonlinear optimization model is developed in this article. The model incorporates the design of forward–reverse manufacturing networks topology, product platform and operation capacity planning. The model takes into account the lead times and costs for each period of planning and is formulated as mixed integer nonlinear programming (MINLP). A two stages branch and bound (B–B) with cutting planes and under-estimators is proposed, which exploits the problem structure by solving problem relaxation at the first stage upper bound (UB) and generates cutting planes and under-estimators at the second stage lower bound (LB). The application in a three-echelon forward–reverse global manufacturing network shows that the proposed algorithm is capable of efficiently handling large scale and non-convex problem formulation in order to achieve a global optimum. Some important results from the model are presented in terms of their impacts on the sustainability of global manufacturing.

      PubDate: 2017-10-11T07:09:30Z
       
  • Stochastic internal rate of return on investments in sustainable assets
           generating carbon credits
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Dileep G. Dhavale, Joseph Sarkis
      Internal rate of return (IRR) is a widely used tool in ranking capital budgeting projects and eventual accept or reject decisions. In this paper, we consider an investment decision involving a sustainable, energy efficient, greenhouse gases (GHG) reducing asset and incorporate the value of carbon emission allowances for the investing company. These allowances create cash flows that may be characterized by significant volatility and uncertainty. The methodology developed in this paper allows decision makers to integrate their knowledge of carbon trading markets and the cash flows that result from sale of emissions credits. The novel methodology utilizes a Bayesian model for IRR that uses Gibbs sampler. Analysis of the results shows that IRR is influenced by volatility and uncertainty of carbon credit cash flows. Ignoring those uncertainty characteristics and simply using the expected values of cash flows can result in significantly inaccurate investment rate of returns. When compared to deterministic IRR calculations, the results show that the occurrence of very high and very low cash flows affects IRR positively, whereas higher variability of cash flow distribution affects IRR of GHG-reducing asset negatively. In other words, frequent large or small cash flows are preferred over fluctuating cash flows. The results may also provide a rationale for the existence of an anomalous consumer behavior known as the energy efficiency gap.

      PubDate: 2017-10-11T07:09:30Z
       
  • Green supplier selection using fuzzy group decision making methods: A case
           study from the agri-food industry
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Narges Banaeian, Hossein Mobli, Behnam Fahimnia, Izabela Ewa Nielsen, Mahmoud Omid
      The incorporation of environmental criteria into the conventional supplier selection practices is essential for organizations seeking to promote green supply chain management. Challenges associated with green supplier selection have been broadly recognized by procurement and supplier management professionals. The development and implementation of practical decision making tools that seek to address these challenges are rapidly evolving. This article contributes to this knowledge area by comparing the application of three popular multi-criteria supplier selection methods in a fuzzy environment. The incorporation of fuzzy set theory into TOPSIS, VIKOR and GRA methods is thoroughly discussed. The methods are then utilized to complete a green supplier evaluation and selection study for an actual company from the agri-food industry. Our comparative analysis for this case study indicates that the three fuzzy methods arrive at identical supplier rankings, yet fuzzy GRA requires less computational complexity to generate the same results. Additional analyses of the numerical results are completed on the normalization functions, distance metrics, and aggregation functions that can be used for each method.

      PubDate: 2017-10-11T07:09:30Z
       
  • Developing a novel model of data envelopment analysis–discriminant
           analysis for predicting group membership of suppliers in sustainable
           supply chain
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Elahe Boudaghi, Reza Farzipoor Saen
      The objective of this paper is to present a novel model of data envelopment analysis–discriminant analysis (DEA–DA) for predicting group membership of suppliers in sustainable supply chain context. Our new model can predict group membership of the suppliers with respect to the nature of factors including inputs, outputs, and efficiency of each supplier. To demonstrate applicability of this new DEA–DA model, using a case study, the initial DEA–DA model developed by Sueyoshi (1999) is analyzed and compared with our proposed model. The results of the analysis show that our new DEA–DA model presents more precise prediction of sustainable suppliers' group membership.

      PubDate: 2017-10-11T07:09:30Z
       
  • Optimal procurement decision with a carbon tax for the manufacturing
           industry
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Xin Ma, Ping Ji, William Ho, Cheng-Hu Yang
      A carbon tax, which has been implemented in several countries, is a cost-effective scheme for reducing carbon emission and developing sustainable supply chains. Two problems, how to make the optimal decision on order quantity and how to select appropriate suppliers for a manufacturer, are studied in this paper in consideration of a carbon tax. For the first problem, a dynamic programming model is developed to study the impact of the carbon tax on calculating the optimal order quantity. In reality, the manufacturer could choose a traditional or a greener supplier. The greener supplier is relatively expensive but yields lower emissions. To obey the emission regulations, the manufacturer should pay for the cost which is incurred by carbon emission. Firstly, in this paper, the expected emission cost is formulated, then, the structural properties of the model are derived. In particular, the optimal order quantity is characterized to minimize the expected total discounted cost. In addition, the effective range of the carbon tax is established to assist government to setup a reasonable carbon tax for a certain industry. For the second problem, a supplier evaluation procedure is proposed to select appropriate suppliers to satisfy the random market demand for the manufacturer. A numerical example from the metal industry is taken to illustrate the properties of the model and the procedure of supplier evaluation. Finally, possible extensions of the model are discussed.

      PubDate: 2017-10-11T07:09:30Z
       
  • Sustainable agro-food supply chain design using two-stage hybrid
           multi-objective decision-making approach
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Hamid Allaoui, Yuhan Guo, Alok Choudhary, Jacqueline Bloemhof
      Sustainability of agro-food supply chains has recently become the subject of greater interest from consumers, firms, governmental organizations and academia as the environment continues to deteriorate. One of the most critical factors influencing the sustainability of an agro-food supply chain is its network design. A particularly challenging aspect in this context is the broad range of influencing indicators associated with the Triple Bottom Line (TBL) of sustainability that need to be considered. However, many of these indicators could not be fully integrated or measured by single-step optimization problems. This paper presents a critical literature review of operational research methods for the design of sustainable supply chains. A novel two-stage hybrid solution methodology is proposed. In the first stage, a partner selection is performed using a hybrid multi criteria decision making based on Analytic Hierarchy Process (AHP) method and the Ordered Weighted Averaging (OWA) aggregation method. The result obtained in the first stage is used in the second stage to develop a multi-objective mathematical model to optimize the design of the supply chain network. This approach allows the simultaneous consideration of all three dimensions of sustainability including carbon footprint, water footprint, number of jobs created and the total cost of the supply chain design. The proposed approach generates a Pareto frontier to aid users in making decisions. Numerical experiments are completed utilizing data from an agro-food company to demonstrate the efficiency and effectiveness of the proposed solution methodology. The analyzes of the numerical results provide important organizational, practical and policy insights on (1) the impact of financial and environmental sustainability on supply chain network design (2) the tradeoff analysis between environmental emission, water footprint, societal implications and associated cost for making informed decision on supply chain investment.

      PubDate: 2017-10-11T07:09:30Z
       
  • A computational study of the general lot-sizing and scheduling model under
           demand uncertainty via robust and stochastic approaches
    • Abstract: Publication date: February 2018
      Source:Computers & Operations Research, Volume 90
      Author(s): Douglas Alem, Eduardo Curcio, Pedro Amorim, Bernardo Almada-Lobo
      This paper presents an empirical assessment of the General Lot-Sizing and Scheduling Problem (GLSP) under demand uncertainty by means of a budget-uncertainty set robust optimization and a two-stage stochastic programming with recourse model. We have also developed a systematic procedure based on Monte Carlo simulation to compare both models in terms of protection against uncertainty and computational tractability. The extensive computational experiments cover different instances characteristics, a considerable number of combinations between budgets of uncertainty and variability levels for the robust optimization model, as well as an increasing number of scenarios and probability distribution functions for the stochastic programming model. Furthermore, we have devised some guidelines for decision-makers to evaluate a priori the most suitable uncertainty modeling approach according to their preferences.

      PubDate: 2017-10-04T06:42:09Z
       
  • Cyclic scheduling of parts and robot moves in m-machine robotic cells
    • Abstract: Publication date: February 2018
      Source:Computers & Operations Research, Volume 90
      Author(s): Hakan Gultekin, Betul Coban, Vahid Eghbal Akhlaghi
      We consider a flow shop type manufacturing cell consisting of m machines and a material handling robot producing multiple parts. The robot transfers the parts between the machines and loads/unloads the machines. We consider the cyclic scheduling of the parts and the robot moves with the objective of maximizing the throughput rate. We develop a mixed integer linear programming formulation of the problem. The formulation is improved with several valid inequalities and reformulations of the constraints. We also develop a hybrid metaheuristic algorithm for this strongly NP-Hard problem. The algorithm is modified to handle both 1-unit and multi-unit robot cycles. Multi-threading is used to parallelize the algorithm in order to improve its efficiency. After calibrating the parameters of the heuristic algorithm, an extensive computational study is performed to evaluate its performance. The results of this study revealed that the developed heuristic provides near-optimal solutions in reasonable solution times. The effects of parallelization and the benefits of considering multi-unit cycles instead of 1-unit cycles are also quantified. Our computational tests show that multi-unit cycles improve the throughput rate by 9% on the average. The improvement can reach to 20% depending on the problem parameters.

      PubDate: 2017-10-04T06:42:09Z
       
  • A hybrid dynamic programming and memetic algorithm to the Traveling
           Salesman Problem with Hotel Selection
    • Abstract: Publication date: February 2018
      Source:Computers & Operations Research, Volume 90
      Author(s): Yongliang Lu, Una Benlic, Qinghua Wu
      The Traveling Salesman Problem with Hotel Selection (TSPHS) is a variant of the classic Traveling Salesman Problem. It arises from a number of real-life applications where the maximum travel time for each “day trip” is limited. In this paper, we present a highly effective hybrid between dynamic programming and memetic algorithm for TSPHS. The main features of the proposed method include a dynamic programming approach to find an optimal hotel sequence for a given tour, three dedicated crossover operators for solution recombination, an adaptive rule for crossover selection, and a two-phase local refinement procedure that alternates between feasible and infeasible searches. Experiments on four sets of 131 benchmark instances from the literature show a remarkable performance of the proposed approach. In particular, it finds improved best solutions for 22 instances and matches the best known results for 103 instances. Additional analyses highlight the contribution of the dynamic programming approach, the joint use of crossovers and the two local search phases to the performance of the proposed algorithm.

      PubDate: 2017-10-04T06:42:09Z
       
  • Exact approaches for the knapsack problem with setups
    • Abstract: Publication date: February 2018
      Source:Computers & Operations Research, Volume 90
      Author(s): Fabio Furini, Michele Monaci, Emiliano Traversi
      We consider a generalization of the knapsack problem in which items are partitioned into classes, each characterized by a fixed cost and capacity. We study three alternative Integer Linear Programming formulations. For each formulation, we design an efficient algorithm to compute the linear programming relaxation (one of which is based on Column Generation techniques). We theoretically compare the strength of the relaxations and derive specific results for a relevant case arising in benchmark instances from the literature. Finally, we embed the algorithms above into a unified implicit enumeration scheme which is run in parallel with an improved Dynamic Programming algorithm to effectively solve the problem to proven optimality. An extensive computational analysis shows that our new exact algorithm is capable of efficiently solving all the instances of the literature and turns out to be the best algorithm for instances with a low number of classes.

      PubDate: 2017-10-04T06:42:09Z
       
  • Improved quick hypervolume algorithm
    • Abstract: Publication date: February 2018
      Source:Computers & Operations Research, Volume 90
      Author(s): Andrzej Jaszkiewicz
      In this paper, we present a significant improvement of the Quick Hypervolume algorithm, one of the state-of-the-art algorithms for calculating the exact hypervolume of the space dominated by a set of d-dimensional points. This value is often used as the quality indicator in the multiobjective evolutionary algorithms and other multiobjective metaheuristics and the efficiency of calculating this indicator is of crucial importance especially in the case of large sets or many dimensional objective spaces. We use a similar divide and conquer scheme as in the original Quick Hypervolume algorithm, but in our algorithm we split the problem into smaller sub-problems in a different way. Through both theoretical analysis and a computational study we show that our approach improves the computational complexity of the algorithm and practical running times.

      PubDate: 2017-09-26T08:04:32Z
       
  • Random partial neighborhood search for the post-enrollment course
           timetabling problem
    • Abstract: Publication date: February 2018
      Source:Computers & Operations Research, Volume 90
      Author(s): Yuichi Nagata
      In this study, we present a local search-based algorithm for the post-enrollment-based course timetabling problem, which incorporates a mechanism for adapting the neighborhood size during the course of the search. At each iteration, the neighborhood size is changed simply by constructing a random partial neighborhood, which is defined as a random subset of the entire neighborhood. The main reason for using a random partial neighborhood is to control the trade-off between exploration and exploitation during search, and two updating strategies are considered for changing the neighborhood size. The proposed algorithms were tested using well-known benchmark sets and the results obtained were highly competitive with those produced by the leading solvers developed for these benchmark sets.

      PubDate: 2017-09-26T08:04:32Z
       
  • Stochastic maximum flow interdiction problems under heterogeneous risk
           preferences
    • Abstract: Publication date: February 2018
      Source:Computers & Operations Research, Volume 90
      Author(s): Xiao Lei, Siqian Shen, Yongjia Song
      We consider a generic maximum flow interdiction problem that involves a leader and a follower who take actions in sequence. Given an interdiction budget, the leader destroys a subset of arcs to minimize the follower’s maximum flows from a source to a sink node. The effect from an interdiction action taken on each arc is random, following a given success rate of decreasing the arc’s capacity to zero. The follower can add additional arc capacities for mitigating flow losses, after knowing the leader’s interdiction plan but before realizing the uncertainty. We consider risk-neutral and risk-averse behaviors of the two players and investigate five bi-level/tri-level programming models for different risk-preference combinations. The models incorporate the expectation, left-tail, and right-tail Conditional Value-at-Risk (CVaR) as commonly used convex risk measures for evaluating random maximum flows in the leader’s and follower’s objectives. We reformulate each model as an equivalent mixed-integer linear program and test them on real-world network instances to demonstrate interactions between the leader and the follower under various risk-preference settings.

      PubDate: 2017-09-26T08:04:32Z
       
  • Total completion time minimization for machine scheduling problem under
           time windows constraints with jobs’ linear processing rate function
    • Abstract: Publication date: February 2018
      Source:Computers & Operations Research, Volume 90
      Author(s): Nhan-Quy Nguyen, Farouk Yalaoui, Lionel Amodeo, Hicham Chehade, Pascal Toggenburger
      In this paper, we consider an identical parallel machine scheduling problem with a single additional resource. The processing rate of a job is defined by a linear resource consumption function. The addressed problem takes into consideration two new constraints. The first is the time-varying total available resource. The second new constraint limits the resource consumption incrementation of each job on two consecutive periods of time. Moreover, jobs have bounded resource consumption, arrival times and deadlines. Many practical applications, such as the electrical charging scheduling, can find interests in our works. Our contributions are two-folds. First, we introduce a Mixed-Integer-Linear-Program (MILP) to formulate the problem. Then, we present a heuristic consisting of two phases: a feasible solution construction phase using geometrical strip packing and a solution improvement phase. The heuristic is proven to be very efficiency for dealing with the problem throughout the numerical experiments.

      PubDate: 2017-09-26T08:04:32Z
       
  • An efficient evolutionary algorithm for the orienteering problem
    • Abstract: Publication date: February 2018
      Source:Computers & Operations Research, Volume 90
      Author(s): Gorka Kobeaga, María Merino, Jose A. Lozano
      This paper deals with the Orienteering Problem, which is a routing problem. In the Orienteering Problem each node has a profit assigned and the goal is to find the route that maximizes the total collected profit subject to a limitation on the total route distance. To solve this problem, we propose an evolutionary algorithm, whose key characteristic is to maintain unfeasible solutions during the search. Furthermore, it includes a novel solution codification for the Orienteering Problem, a novel heuristic for node inclusion in the route, an adaptation of the Edge Recombination crossover developed for the Travelling Salesperson Problem, specific operators to recover the feasibility of solutions when required, and the use of the Lin-Kernighan heuristic to improve the route lengths. We compare our algorithm with three state-of-the-art algorithms for the problem on 344 benchmark instances, with up to 7397 nodes. The results show a competitive behavior of our approach in instances of low-medium dimensionality, and outstanding results in the large dimensionality instances reaching new best known solutions with lower computational time than the state-of-the-art algorithms.

      PubDate: 2017-09-20T07:50:06Z
       
  • Preemptive rerouting of airline passengers under uncertain delays
    • Abstract: Publication date: February 2018
      Source:Computers & Operations Research, Volume 90
      Author(s): Lindsey A. McCarty, Amy E.M. Cohn
      An airline’s operational disruptions can lead to flight delays that in turn impact passengers, not only through the delays themselves but also through possible missed connections. Since the length of a delay is often not known in advance, we consider preemptive rerouting of airline passengers before the length of the delay is realized. Our goal is to reaccommodate passengers proactively as soon as it is known that a flight will be delayed instead of waiting until passengers have missed connections. We consider the simplified version of the real-world problem in which only a single flight is delayed. We model this problem as a two-stage stochastic programming problem, with first-stage decisions that may preemptively assign passengers to new itineraries in anticipation of the delay’s impact, and second-stage decisions that may further modify itineraries for any passengers who still miss connections after the delay has been realized. We present a Benders Decomposition approach to solving this problem and give computational results to demonstrate the reasonable run time in solving our model. This research lays the groundwork for the more-realistic case in which multiple flights in the network may experience concurrent delays.

      PubDate: 2017-09-14T07:48:29Z
       
  • Enhancing urban mobility: Integrating ride-sharing and public transit
    • Abstract: Publication date: February 2018
      Source:Computers & Operations Research, Volume 90
      Author(s): Mitja Stiglic, Niels Agatz, Martin Savelsbergh, Mirko Gradisar
      Seamless integration of ride-sharing and public transit may offer fast, reliable, and affordable transfer to and from transit stations in suburban areas thereby enhancing mobility of residents. We investigate the potential benefits of such a system, as well as the ride-matching technology required to support it, by means of an extensive computational study. Our study shows that the integration of a ride-sharing system and a public transit system can significantly enhance mobility and increase the use of public transport.

      PubDate: 2017-09-14T07:48:29Z
       
  • A bi-criteria hybrid Genetic Algorithm with robustness objective for the
           course timetabling problem
    • Abstract: Publication date: February 2018
      Source:Computers & Operations Research, Volume 90
      Author(s): Can Akkan, Ayla Gülcü
      Traditional methods of generating timetables may yield high-quality solutions, but they may not yield robust solutions that may easily be adapted to changing inputs. Incorporating late changes by making minimum modifications on the final timetable is an important need in many practical applications of timetabling. In this study, we focus on a subset of course timetabling problems, the curriculum-based timetabling problem. We first define a robustness measure for the problem, and then try to find a set of good solutions in terms of both penalty and robustness values. We model the problem as a bi-criteria optimization problem and solve it by a hybrid Multi-objective Genetic Algorithm, which makes use of Hill Climbing and Simulated Annealing algorithms in addition to the standard Genetic Algorithm approach. The algorithm is tested on the well known ITC-2007 instances and shown to identify high quality Pareto fronts.

      PubDate: 2017-09-14T07:48:29Z
       
  • Minimizing the tracking error of cardinality constrained portfolios
    • Abstract: Publication date: February 2018
      Source:Computers & Operations Research, Volume 90
      Author(s): Purity Mutunge, Dag Haugland
      We study the problem of selecting a restricted number of shares included in a stock market index, such that the portfolio resembles the index as closely as possible. To measure the difference between the portfolio and the index, referred to as the tracking error, we use a quadratic function with the covariance matrix of the index returns as coefficient matrix. The problem is proved to be strongly NP-hard, and we give theoretical evidence that continuous relaxations of mixed integer quadratic programming (MIQP) formulations are likely to produce poor lower bounds on the tracking error. For fast computation of near-optimal portfolios, we demonstrate how the best-extension-by-one construction heuristic can be designed to run in time bounded by a fourth order polynomial. We also show that the running time of one iteration of the best-exchange-by one improvement heuristic is of the same order. Computational experiments applied to real-life stock market indices show that in instances where an index of less than 500 assets is to be tracked by a portfolio of 10 assets, a commercially available MIQP solver fails to reduce the integrality gap below 94% in 30 CPU-minutes. In contrast, the construction heuristic under study needs less than 30 CPU-seconds to produce a portfolio of 100 assets tracking an index of nearly 2000 assets.

      PubDate: 2017-09-14T07:48:29Z
       
  • New insights on the block relocation problem
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Fabien Tricoire, Judith Scagnetti, Andreas Beham
      This article presents new methods for the block relocation problem (BRP). Although much of the existing work focuses on the restricted BRP, we tackle the unrestricted BRP, which yields more opportunities for optimisation. Our contributions include fast heuristics able to tackle very large instances within seconds, fast metaheuristics that provide very competitive performance on benchmark data sets, as well as a new lower bound that generalises existing ones. We embed it in a branch-and-bound algorithm, then assess the influence of various factors on the efficiency of branch-and-bound algorithms for the BRP.

      PubDate: 2017-09-08T07:45:48Z
       
  • A branch-and-cut algorithm for the Time Window Assignment Vehicle Routing
           Problem
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Kevin Dalmeijer, Remy Spliet
      This paper presents a branch-and-cut algorithm for the Time Window Assignment Vehicle Routing Problem (TWAVRP), the problem of assigning time windows for delivery before demand volume becomes known. A novel set of valid inequalities, the precedence inequalities, is introduced and multiple separation heuristics are presented. In our numerical experiments the branch-and-cut algorithm is 3.8 times faster when separating precedence inequalities. Furthermore, in our experiments, the branch-and-cut algorithm is 193.9 times faster than the best known algorithm in the literature. Finally, using our algorithm, instances of the TWAVRP are solved which are larger than the instances previously presented in the literature.

      PubDate: 2017-09-08T07:45:48Z
       
  • Flexible solutions to maritime inventory routing problems with delivery
           time windows
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Chengliang Zhang, George Nemhauser, Joel Sokol, Myun-Seok Cheon, Ahmet Keha
      This paper studies a Maritime Inventory Routing Problem with Time Windows (MIRPTW) for deliveries with uncertain disruptions. We consider disruptions that increase travel times between ports and ultimately affect the deliveries in one or more time windows. The objective is to find flexible solutions that can accommodate unplanned disruptions. We propose a Lagrangian heuristic algorithm for obtaining flexible solutions by introducing auxiliary soft constraints that are incorporated in the objective function with Lagrange multipliers. To evaluate the flexibility of solutions, we build a simulator that generates disruptions and recovery solutions. Computational results show that by incurring a small increase in initial cost (sometimes zero), our planning strategies generate solutions that are often significantly less vulnerable to potential disruptions. We also consider the effect of lead time in being able to respond to the disruptions.

      PubDate: 2017-09-08T07:45:48Z
       
  • A linear programming based algorithm to solve a class of optimization
           problems with a multi-linear objective function and affine constraints
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Hadi Charkhgard, Martin Savelsbergh, Masoud Talebian
      We present a linear programming based algorithm for a class of optimization problems with a multi-linear objective function and affine constraints. This class of optimization problems has only one objective function, but it can also be viewed as a class of multi-objective optimization problems by decomposing its objective function. The proposed algorithm exploits this idea and solves this class of optimization problems from the viewpoint of multi-objective optimization. The algorithm computes an optimal solution when the number of variables in the multi-linear objective function is two, and an approximate solution when the number of variables is greater than two. A computational study demonstrates that when available computing time is limited the algorithm significantly outperforms well-known convex programming solvers IPOPT and CVXOPT, in terms of both efficiency and solution quality. The optimization problems in this class can be reformulated as second-order cone programs, and, therefore, also be solved by second-order cone programming solvers. This is highly effective for small and medium size instances, but we demonstrate that for large size instances with two variables in the multi-linear objective function the proposed algorithm outperforms a (commercial) second-order cone programming solver.

      PubDate: 2017-09-02T07:40:44Z
       
  • Benders decomposition applied to a robust multiple allocation incomplete
           hub location problem
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Elisangela Martins de Sá, Reinaldo Morabito, Ricardo Saraiva de Camargo
      This paper focuses on a multiple allocation incomplete hub location problem in which a hub network can be partially interconnected by hub arcs, direct connections between non-hub nodes are allowed, and uncertainty is assumed for the data of origin-destination demands and hub fixed costs. This problem consists of locating hubs, activating hub arcs and routing the demand flows over the designed network such that the total cost is minimized. The total cost is composed of fixed setup costs for hubs and hub arcs, and of transportation costs. This problem has economical and social appeals for designers of public transportation systems and other hub networks. A robust optimization approach is chosen to address the data uncertainty considering that demand flows and fixed setup costs are not known with certainty in advance. The computational experiments on benchmark instances from the hub location literature showed that the proposed robust model renders better assurance of not violating budget constraints than the deterministic version. Further, two specialized Benders decomposition frameworks and an ILS-VND stochastic local search procedure are also devised to tackle larger problem instances with up to 100 nodes in reasonable computational times.

      PubDate: 2017-09-02T07:40:44Z
       
  • Workload smoothing in simple assembly line balancing
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Meral Azizoğlu, Sadullah İmat
      This paper considers a simple assembly line balancing problem with fixed number of workstations and prespecified cycle time. Our objective is to minimize the sum of the squared deviations of the workstation loads around the cycle time, hence maintain workload smoothing. We develop several optimality properties and bounding mechanisms, and use them in our branch and bound algorithm. The results of our computational study reveal that our branch and bound algorithm is capable of solving medium sized problem instances in reasonable times.

      PubDate: 2017-09-02T07:40:44Z
       
  • Corridor-based metro network design with travel flow capture
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Gabriel Gutiérrez-Jarpa, Gilbert Laporte, Vladimir Marianov
      We consider a metro network design problem in which the objective is to maximize the origin/destination traffic captured by the system. The lines of the network are located within some corridors that are also determined by the procedure. The amount of captured traffic depends on the ratio between travel time by metro and travel time using alternative modes. There is a limited construction budget. Lower bounds are imposed on the angles between alignments, which allows the generation of different network shapes. A matheuristic is proposed to solve the problem. The method is applied to a test case from the city of Concepción, Chile.

      PubDate: 2017-09-02T07:40:44Z
       
  • Stochastic local search with learning automaton for the swap-body vehicle
           routing problem
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Túlio A.M. Toffolo, Jan Christiaens, Sam Van Malderen, Tony Wauters, Greet Vanden Berghe
      This work presents the stochastic local search method for the Swap-Body Vehicle Routing Problem (SB-VRP) that won the First VeRoLog Solver Challenge. The SB-VRP, proposed on the occasion of the challenge, is a generalization of the classical Vehicle Routing Problem (VRP) in which customers are served by vehicles whose sizes may be enlarged via the addition of a swap body (trailer). The inclusion of a swap body doubles vehicle capacity while also increasing its operational cost. However, not all customers may be served by vehicles consisting of two bodies. Therefore swap locations are present where one of the bodies may be temporarily parked, enabling double body vehicles to serve customers requiring a single body. Both total travel time and distance incur costs that should be minimized, while the number of customers visited by a single vehicle is limited both by its capacity and by a maximum travel time. State of the art VRP approaches do not accommodate SB-VRP generalizations well. Thus, dedicated approaches taking advantage of the swap body characteristic are desired. The present paper proposes a stochastic local search algorithm with both general and dedicated heuristic components, a subproblem optimization scheme and a learning automaton. The algorithm improves the best known solution for the majority of the instances proposed during the challenge. Results are also presented for a new set of instances with the aim of stimulating further research concerning the SB-VRP.

      PubDate: 2017-09-02T07:40:44Z
       
  • Compressed data structures for bi-objective {0,1}-knapsack problems
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Pedro Correia, Luís Paquete, José Rui Figueira
      Solving multi-objective combinatorial optimization problems to optimality is a computationally expensive task. The development of implicit enumeration approaches that efficiently explore certain properties of these problems has been the main focus of recent research. This article proposes algorithmic techniques that extend and empirically improve the memory usage of a dynamic programming algorithm for computing the set of efficient solutions both in the objective space and in the decision space for the bi-objective knapsack problem. An in-depth experimental analysis provides further information about the performance of these techniques with respect to the trade-off between CPU time and memory usage.

      PubDate: 2017-09-02T07:40:44Z
       
  • Multi-commodity location-routing: Flow intercepting formulation and
           branch-and-cut algorithm
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Maurizio Boccia, Teodor Gabriel Crainic, Antonio Sforza, Claudio Sterle
      Research on the location-routing problem (LRP) is very active, producing a good number of effective exact and approximated solution approaches. It is noteworthy that most of the contributions present in the literature address the single-commodity LRP, whereas the multi-commodity case has been scarcely investigated. Yet, this issue assumes an important role in many LRP applications, particularly in the context of designing single-tier freight distribution City Logistics systems. To fill this gap, we define a new multi-commodity LRP, proposing an original integer linear programming model for it. The proposed formulation takes into account the multi-commodity feature of the problem, modeling the strategic location and the tactical routing decisions using the flow intercepting approach. We therefore name this problem the flow intercepting facility location-routing problem. It is solved by a branch-and-cut algorithm which exploits cuts derived and adapted from literature. The proposed method is successfully experienced and validated on test instances reproducing different network topologies and problem settings.

      PubDate: 2017-09-02T07:40:44Z
       
  • Satisfiability modulo theory (SMT) formulation for optimal scheduling of
           task graphs with communication delay
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Avinash Malik, Cameron Walker, Michael O’Sullivan, Oliver Sinnen
      In scheduling theory and practise for parallel computing, representing a program as a task graph with communication delays is a popular model, due to its general nature, its expressiveness and relative simplicity. Unfortunately, scheduling such a task graph on a set of processors in such a way that it achieves its shortest possible execution time (P pred, cij C max  in α β γ notation) is a strong NP-hard optimization problem without any known guaranteed approximation algorithm. Hence, many heuristics have been researched and are used in practise. However, in many situations it is necessary to obtain optimal schedules, for example, in the case of time-critical systems or for the evaluation of heuristics. Recent years have seen some advances in optimal algorithms for this scheduling problem, based on smart exhaustive state-space search or MILP (Mixed Integer Linear Programming) formulations. This paper proposes a novel approach based on SMT (Satisfiability Modulo Theory). We propose an elegant SMT formulation of the scheduling problem that only needs one decision variable and is very compact and comprehensible in comparison to the state-of-the-art MILP formulations. This novel optimal scheduling approach is extensively evaluated in experiments with more than a thousand task graphs. We perform experimental comparison with the best known MILP formulations, with attempts to further improve them, and deeply analyse the behaviour of the different approaches with respect to size, structure, number of processors, etc. Our proposed SMT-based approach in general outperforms the MILP-formulations and still possesses great potential for further optimization, from which MILP formulations have benefited in the past.

      PubDate: 2017-09-02T07:40:44Z
       
  • Metaheuristics for the tabu clustered traveling salesman problem
    • Abstract: Publication date: January 2018
      Source:Computers & Operations Research, Volume 89
      Author(s): Tianjiao Zhang, Liangjun Ke, Jing Li, Jisheng Li, Jingqi Huang, Zexi Li
      This paper considers a new variant of traveling salesman problem (TSP), called tabu clustered TSP (TCTSP). The nodes in TCTSP are partitioned into two kinds of subsets: clusters and tabu node sets, then the salesman has to visit exactly one node for each tabu node set and ensures that the nodes within a same cluster are visited consecutively, and the problem calls for a minimum cost cycle. The TCTSP can be used to model a class of telemetry tracking and command (TT&C) resources scheduling problem (TTCRSP), the goal of which is to efficiently schedule the TT&C resources in order to enable the satellites to be operated normally in their designed orbits. To solve it, two metaheuristics combined with path relinking are proposed. The one is Ant Colony Optimization (ACO) and the other is Greedy Randomized Adaptive Search Procedure (GRASP). The proposed algorithms are tested on the benchmark instances and real-life instances of the TTCRSP. The computational results show that the hybrid ACO with two path relinking strategies works the best among the studied metaheuristics in terms of solution quality within the same computational time.

      PubDate: 2017-08-03T06:22:10Z
       
  • Network design in scarce data environment using moment-based
           distributionally robust optimization
    • Abstract: Publication date: December 2017
      Source:Computers & Operations Research, Volume 88
      Author(s): Hideaki Nakao, Siqian Shen, Zhihao Chen
      We consider a network design problem (NDP) under random demand with unknown distribution for which only a small number of observations are known. We design arc capacities in the first stage and optimize single-commodity network flows after realizing the demand in the second stage. The objective is to minimize the total cost of allocating arc capacities, flowing commodities, and penalty for unmet demand. We formulate a distributionally robust NDP (DR-NDP) by constructing an ambiguity set of the unknown demand distribution based on marginal moment information, to minimize the worst-case total cost over all possible distributions. Approximating polynomials with piecewise-linear functions, we reformulate DR-NDP as a mixed-integer linear program optimized via a cutting-plane algorithm. We test diverse network instances to compare DR-NDP with a stochastic programming approach, a deterministic benchmark model, and a robust NDP formulation. Our results demonstrate adequate robustness of optimal DR-NDP solutions and how they perform under varying demand, modeling parameter, network, and cost settings. The results highlight potential niche uses of DR-NDP in data-scarce contexts.

      PubDate: 2017-07-09T09:05:39Z
       
  • An adaptive large neighborhood search for the full truckload pickup and
           delivery problem with resource synchronization
    • Abstract: Publication date: December 2017
      Source:Computers & Operations Research, Volume 88
      Author(s): Axel Grimault, Nathalie Bostel, Fabien Lehuédé
      This paper presents the Full Truckload Pickup and Delivery Problem with Resource Synchronization (FT-PDP-RS). It consists of optimizing the transport of materials between sites, using a heterogeneous fleet of trucks, in the context of public works. Full truckload pickup and delivery requests have to be served within time windows. Trucks are synchronized on pickup or delivery locations based on unitary loading and unloading resources. We propose an Adaptive Large Neighborhood Search (ALNS) to solve this problem. Custom destroy and repair operators and an efficient feasibility insertion procedure have been designed to solve it. The method has been evaluated on real instances from the literature and on real case instances from a public works company. Computational experiments confirm the efficiency of the method.

      PubDate: 2017-06-28T22:14:08Z
       
  • A distance-limited continuous location-allocation problem for spatial
           planning of decentralized systems
    • Abstract: Publication date: December 2017
      Source:Computers & Operations Research, Volume 88
      Author(s): Kagan Gokbayrak, Ayse Selin Kocaman
      We introduce a new continuous location-allocation problem where the facilities have both a fixed opening cost and a coverage distance limitation. The problem has wide applications especially in the spatial planning of water and/or energy access networks where the coverage distance might be associated with the physical loss constraints. We formulate a mixed integer quadratically constrained problem (MIQCP) under the Euclidean distance setting and present a three-stage heuristic algorithm for its solution: In the first stage, we solve a planar set covering problem (PSCP) under the distance limitation. In the second stage, we solve a discrete version of the proposed problem where the set of candidate locations for the facilities is formed by the union of the set of demand points and the set of locations in the PSCP solution. Finally, in the third stage, we apply a modified Weiszfeld’s algorithm with projections that we propose to incorporate the coverage distance component of our problem for fine-tuning the discrete space solutions in the continuous space. We perform numerical experiments on three example data sets from the literature to demonstrate the performance of the suggested heuristic method.

      PubDate: 2017-06-28T22:14:08Z
       
  • Integrating dock-door assignment and vehicle routing with cross-docking
    • Abstract: Publication date: December 2017
      Source:Computers & Operations Research, Volume 88
      Author(s): Furkan Enderer, Claudio Contardo, Ivan Contreras
      This paper presents an integrated cross-dock door assignment and vehicle routing problem arising in the operation of cross-dock terminals. It consists of assigning origins to inbound doors, transferring commodities between doors, and routing vehicles from outbound doors to destinations. The objective is to jointly minimize the total material handling and transportation costs. Two formulations of the problem are presented and computationally compared. In addition, we develop a column generation algorithm based on the most promising formulation and a heuristic to obtain lower and upper bounds for the optimal solution of the problem, respectively. Numerical results on a set of benchmark instances with up to 20 origins and 50 destinations confirm the efficiency of the proposed solution algorithms.

      PubDate: 2017-06-28T22:14:08Z
       
 
 
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