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  Subjects -> BUSINESS AND ECONOMICS (Total: 3251 journals)
    - ACCOUNTING (100 journals)
    - BANKING AND FINANCE (275 journals)
    - BUSINESS AND ECONOMICS (1195 journals)
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    - PUBLIC FINANCE, TAXATION (36 journals)
    - TRADE AND INDUSTRIAL DIRECTORIES (2 journals)

BUSINESS AND ECONOMICS (1195 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: 10)
Abacus     Hybrid Journal   (Followers: 13)
Accounting Forum     Hybrid Journal   (Followers: 25)
Acta Amazonica     Open Access   (Followers: 5)
Acta Commercii     Open Access   (Followers: 4)
Acta Oeconomica     Full-text available via subscription   (Followers: 2)
Acta Scientiarum. Human and Social Sciences     Open Access   (Followers: 8)
Acta Universitatis Danubius. Œconomica     Open Access   (Followers: 3)
Acta Universitatis Nicolai Copernici Zarządzanie     Open Access   (Followers: 4)
AD-minister     Open Access   (Followers: 3)
Admisi dan Bisnis     Open Access  
ADR Bulletin     Open Access   (Followers: 5)
Advances in Developing Human Resources     Hybrid Journal   (Followers: 23)
Advances in Economics and Business     Open Access   (Followers: 13)
AfricaGrowth Agenda     Full-text available via subscription   (Followers: 1)
African Affairs     Hybrid Journal   (Followers: 65)
African Development Review     Hybrid Journal   (Followers: 36)
African Journal of Business and Economic Research     Full-text available via subscription   (Followers: 3)
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: 10)
Akademika : Journal of Southeast Asia Social Sciences and Humanities     Open Access   (Followers: 7)
Alphanumeric Journal : The Journal of Operations Research, Statistics, Econometrics and Management Information Systems     Open Access   (Followers: 5)
American Economic Journal : Applied Economics     Full-text available via subscription   (Followers: 176)
American Enterprise Institute     Free  
American Journal of Business     Hybrid Journal   (Followers: 17)
American Journal of Business and Management     Open Access   (Followers: 53)
American Journal of Business Education     Open Access   (Followers: 12)
American Journal of Economics and Business Administration     Open Access   (Followers: 26)
American Journal of Economics and Sociology     Hybrid Journal   (Followers: 30)
American Journal of Evaluation     Hybrid Journal   (Followers: 14)
American Journal of Finance and Accounting     Hybrid Journal   (Followers: 21)
American Journal of Health Economics     Full-text available via subscription   (Followers: 13)
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: 27)
ANALES de la Universidad Central del Ecuador     Open Access   (Followers: 3)
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: 29)
Annals of Operations Research     Hybrid Journal   (Followers: 10)
Annual Review of Economics     Full-text available via subscription   (Followers: 32)
Anuario Facultad de Ciencias Económicas y Empresariales     Open Access   (Followers: 2)
Applied Developmental Science     Hybrid Journal   (Followers: 3)
Applied Economics     Hybrid Journal   (Followers: 42)
Applied Economics Letters     Hybrid Journal   (Followers: 29)
Applied Economics Quarterly     Full-text available via subscription   (Followers: 9)
Applied Financial Economics     Hybrid Journal   (Followers: 25)
Applied Mathematical Finance     Hybrid Journal   (Followers: 8)
Applied Stochastic Models in Business and Industry     Hybrid Journal   (Followers: 6)
Arab Economic and Business Journal     Open Access   (Followers: 4)
Archives of Business Research     Open Access   (Followers: 6)
Arena Journal     Full-text available via subscription   (Followers: 1)
Argomenti. Rivista di economia, cultura e ricerca sociale     Open Access   (Followers: 4)
ASEAN Economic Bulletin     Full-text available via subscription   (Followers: 5)
Asia Pacific Business Review     Hybrid Journal   (Followers: 7)
Asia Pacific Journal of Human Resources     Hybrid Journal   (Followers: 321)
Asia Pacific Journal of Innovation and Entrepreneurship     Open Access  
Asia Pacific Viewpoint     Hybrid Journal   (Followers: 1)
Asia-Pacific Journal of Business Administration     Hybrid Journal   (Followers: 5)
Asia-Pacific Journal of Operational Research     Hybrid Journal   (Followers: 3)
Asia-Pacific Management and Business Application     Open Access   (Followers: 1)
Asian Business Review     Open Access   (Followers: 3)
Asian Case Research Journal     Hybrid Journal   (Followers: 1)
Asian Development Review     Open Access   (Followers: 13)
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: 3)
Asian Journal of Business Ethics     Hybrid Journal   (Followers: 9)
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)
ATA Journal of Legal Tax Research     Full-text available via subscription   (Followers: 4)
Atlantic Economic Journal     Hybrid Journal   (Followers: 11)
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: 32)
Australian Economic Review     Hybrid Journal   (Followers: 3)
Australian Journal of Maritime and Ocean Affairs     Hybrid Journal   (Followers: 9)
Balkan Region Conference on Engineering and Business Education     Open Access   (Followers: 1)
Baltic Journal of Real Estate Economics and Construction Management     Open Access   (Followers: 2)
Banks in Insurance Report     Hybrid Journal   (Followers: 1)
BBR - Brazilian Business Review     Open Access   (Followers: 4)
Benchmarking : An International Journal     Hybrid Journal   (Followers: 10)
Benefit : Jurnal Manajemen dan Bisnis     Open Access   (Followers: 1)
BER : Consumer Confidence Survey     Full-text available via subscription   (Followers: 3)
BER : Economic Prospects : An Executive Summary     Full-text available via subscription  
BER : Economic Prospects : Full Survey     Full-text available via subscription   (Followers: 1)
BER : Intermediate Goods Industries Survey     Full-text available via subscription  
BER : Manufacturing Survey : Full Survey     Full-text available via subscription   (Followers: 1)
BER : Motor Trade Survey     Full-text available via subscription  
BER : Retail Sector Survey     Full-text available via subscription   (Followers: 1)
BER : Retail Survey : Full Survey     Full-text available via subscription   (Followers: 1)
BER : Survey of Business Conditions in Building and Construction : An Executive Summary     Full-text available via subscription   (Followers: 3)
BER : Survey of Business Conditions in Manufacturing : An Executive Summary     Full-text available via subscription   (Followers: 2)
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: 1)
BER : Wholesale Sector Survey     Full-text available via subscription  
Berkeley Business Law Journal     Free   (Followers: 9)
Bio-based and Applied Economics     Open Access   (Followers: 1)
Biodegradation     Hybrid Journal   (Followers: 1)
Biology Direct     Open Access   (Followers: 7)
BizInfo (Blace) Journal of Economics, Management and Informatics     Open Access  
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: 4)
Briefings in Real Estate Finance     Hybrid Journal   (Followers: 5)
British Journal of Industrial Relations     Hybrid Journal   (Followers: 36)
Brookings Papers on Economic Activity     Open Access   (Followers: 46)
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: 5)
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: 19)
Business & Information Systems Engineering     Hybrid Journal   (Followers: 4)
Business & Society     Hybrid Journal   (Followers: 10)
Business : Theory and Practice / Verslas : Teorija ir Praktika     Open Access   (Followers: 1)
Business and Economic Research     Open Access   (Followers: 7)
Business and Management Horizons     Open Access   (Followers: 12)
Business and Management Research     Open Access   (Followers: 18)
Business and Management Studies     Open Access   (Followers: 11)
Business and Politics     Hybrid Journal   (Followers: 8)
Business and Professional Communication Quarterly     Hybrid Journal   (Followers: 7)
Business and Society Review     Hybrid Journal   (Followers: 5)
Business Economics     Hybrid Journal   (Followers: 9)
Business Ethics Quarterly     Full-text available via subscription   (Followers: 13)
Business Ethics: A European Review     Hybrid Journal   (Followers: 18)
Business Horizons     Hybrid Journal   (Followers: 8)
Business Information Review     Hybrid Journal   (Followers: 14)
Business Management and Strategy     Open Access   (Followers: 41)
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: 17)
Business, Peace and Sustainable Development     Full-text available via subscription   (Followers: 3)
Bustan     Hybrid Journal  
Cadernos EBAPE.BR     Open Access   (Followers: 1)
Cambridge Journal of Economics     Hybrid Journal   (Followers: 61)
Cambridge Journal of Regions, Economy and Society     Hybrid Journal   (Followers: 10)
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: 29)
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: 17)
Case Studies in Business and Management     Open Access   (Followers: 10)
CBU International Conference Proceedings     Open Access   (Followers: 3)
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: 17)
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: 19)
China Economic Journal: The Official Journal of the China Center for Economic Research (CCER) at Peking University     Hybrid Journal   (Followers: 13)
China Economic Review     Hybrid Journal   (Followers: 10)
China Finance Review International     Hybrid Journal   (Followers: 5)
China Nonprofit Review     Hybrid Journal   (Followers: 3)
China perspectives     Open Access   (Followers: 12)
Chinese Economy     Full-text available via subscription  
Ciência & Saúde Coletiva     Open Access   (Followers: 2)
CLIO América     Open Access   (Followers: 1)
Cliometrica     Hybrid Journal   (Followers: 4)
COEPTUM     Open Access  
Community Development Journal     Hybrid Journal   (Followers: 27)
Compensation & Benefits Review     Hybrid Journal   (Followers: 7)
Competition & Change     Hybrid Journal   (Followers: 11)
Competitive Intelligence Review     Hybrid Journal   (Followers: 2)
Competitiveness Review : An International Business Journal incorporating Journal of Global Competitiveness     Hybrid Journal   (Followers: 5)
Computational Economics     Hybrid Journal   (Followers: 9)
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 8)
Computer Law & Security Review     Hybrid Journal   (Followers: 17)
Computers & Operations Research     Hybrid Journal   (Followers: 12)
Construction Innovation: Information, Process, Management     Hybrid Journal   (Followers: 14)
Contemporary Wales     Full-text available via subscription   (Followers: 1)
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: 7)
Corporate Philanthropy Report     Hybrid Journal   (Followers: 2)
Corporate Reputation Review     Hybrid Journal   (Followers: 5)
Creative and Knowledge Society     Open Access   (Followers: 9)
Creative Industries Journal     Hybrid Journal   (Followers: 8)
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: 5)
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)

        1 2 3 4 5 6 | Last

Journal Cover Computers & Operations Research
  [SJR: 2.237]   [H-I: 104]   [12 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0305-0548
   Published by Elsevier Homepage  [3175 journals]
  • Designing new heuristics for the capacitated lot sizing problem by genetic
           programming
    • Authors: Fanny Hein; Christian Almeder; Gonçalo Figueira; Bernardo Almada-Lobo
      Pages: 1 - 14
      Abstract: Publication date: August 2018
      Source:Computers & Operations Research, Volume 96
      Author(s): Fanny Hein, Christian Almeder, Gonçalo Figueira, Bernardo Almada-Lobo
      This work addresses the well-known capacitated lot sizing problem (CLSP) which is proven to be an NP-hard optimization problem. Simple period-by-period heuristics are popular solution approaches due to the extremely low computational effort and their suitability for rolling planning horizons. The aim of this work is to apply genetic programming (GP) to automatically generate specialized heuristics specific to the instance class. Experiments show that we are able to obtain better solutions when using GP evolved lot sizing rules compared to state-of-the-art constructive heuristics.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.03.006
      Issue No: Vol. 96 (2018)
       
  • Reliable single allocation hub location problem under hub breakdowns
    • Authors: Borzou Rostami; Nicolas Kämmerling; Christoph Buchheim; Uwe Clausen
      Pages: 15 - 29
      Abstract: Publication date: August 2018
      Source:Computers & Operations Research, Volume 96
      Author(s): Borzou Rostami, Nicolas Kämmerling, Christoph Buchheim, Uwe Clausen
      The design of hub-and-spoke transport networks is a strategic planning problem, as the choice of hub locations has to remain unchanged for long time periods. However, strikes, disasters or traffic breakdown can lead to the unavailability of a hub for a short period of time. Therefore it is important to consider such events already in the planning phase, so that a proper reaction is possible; once a hub breaks down, an emergency plan has to be applied to handle the flows that were scheduled to be served by this hub. In this paper, we develop a two-stage formulation for the single allocation hub location problem which includes the reallocation of sources to a backup hub in case the hub breaks down. In contrast to related problem formulations from the literature, we keep the non-linear structure of the problem in our model. A branch-and-cut framework based on Benders decomposition is designed to solve large scale instances to proven optimality. Thanks to our decomposition strategy, we keep the structure of the resulting formulation similar to the classical single allocation hub location problem, which in turn allows to use classical linearization techniques from the literature. Our computational experiments show that this approach leads to a significant improvement in the performance when embedded into a standard mixed-integer programming solver. We report optimal solutions for instances much bigger than those solved so far in the literature.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.04.002
      Issue No: Vol. 96 (2018)
       
  • Solving a selective dial-a-ride problem with logic-based Benders
           decomposition
    • Authors: Martin Riedler; Günther Raidl
      Pages: 30 - 54
      Abstract: Publication date: August 2018
      Source:Computers & Operations Research, Volume 96
      Author(s): Martin Riedler, Günther Raidl
      Today’s society is facing an ever-growing demand for mobility. To a high degree these needs can be fulfilled by individual and public transport. People that do not have access to the former and cannot use the latter require additional means of transportation. This is where dial-a-ride services come into play. The dial-a-ride problem considers transportation requests of people from pick-up to drop-off locations. Users specify time windows with respect to these points. Requests are served by a given vehicle fleet with limited capacity and tour duration per vehicle. Moreover, user inconvenience considerations are taken into account by limiting the travel time between origin and destination for each request. Previous research on the dial-a-ride problem primarily focused on serving a given set of requests with a fixed-size vehicle fleet at minimal traveling costs. It is assumed that the request set is sufficiently small to be served by the available vehicles. We consider a different scenario in which a maximal number of requests shall be served under the given constraints, i.e., it is no longer guaranteed that all requests can be accepted. For this new problem variant we propose a compact mixed integer linear programming model as well as algorithms based on Benders decomposition. In particular, we employ logic-based Benders decomposition and branch-and-check using mixed integer linear programming and constraint programming algorithms. We consider different variants on how to generate Benders cuts as well as heuristic boosting techniques and different types of valid inequalities. Computational experiments illustrate the effectiveness of the suggested algorithms.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.03.008
      Issue No: Vol. 96 (2018)
       
  • A multi-objective differential evolution algorithm for parallel batch
           processing machine scheduling considering electricity consumption cost
    • Authors: Shengchao Zhou; Xiaolin Li; Ni Du; Yan Pang; Huaping Chen
      Pages: 55 - 68
      Abstract: Publication date: August 2018
      Source:Computers & Operations Research, Volume 96
      Author(s): Shengchao Zhou, Xiaolin Li, Ni Du, Yan Pang, Huaping Chen
      The manufacturing industry consumes massive amounts of energy and produces great numbers of greenhouse gases every year. Recently, an increasing attention has been paid to the energy efficiency of the manufacturing industry. This paper considers a parallel batch processing machine (BPM) scheduling problem in the presence of dynamic job arrivals and a time-of-use pricing scheme. The objective is to simultaneously minimize makespan, a measure of production efficiency and minimize total electricity cost (TEC), an indicator for environmental sustainability. A BPM is capable of processing multiple jobs at a time, which has wide applications in many manufacturing industries such as electronics manufacturing facilities and steel-making plants. We formulate this problem as a mixed integer programming model. Considering the problem is strongly NP-hard, a multi-objective differential evolution algorithm is proposed for effectively solving the problem at large scale. The performance of the proposed algorithm is evaluated by comparing it to the well-known NSGA-II algorithm and another multi-objective optimization algorithm AMGA. Experimental results show that the proposed algorithm performs better than NSGA-II and AMGA in terms of solution quality and distribution.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.04.009
      Issue No: Vol. 96 (2018)
       
  • Multiple domination models for placement of electric vehicle charging
           stations in road networks
    • Authors: Andrei Gagarin; Padraig Corcoran
      Pages: 69 - 79
      Abstract: Publication date: August 2018
      Source:Computers & Operations Research, Volume 96
      Author(s): Andrei Gagarin, Padraig Corcoran
      Electric and hybrid vehicles play an increasing role in road transport networks. Despite their advantages, they have a relatively limited cruising range in comparison to traditional diesel/petrol vehicles, and require significant battery charging time. We propose to model the facility location problem of the placement of charging stations in road networks as a multiple domination problem on reachability graphs. This model takes into consideration natural assumptions such as a threshold for remaining battery charge, and provides some minimal choice for a travel direction to recharge the battery. Experimental evaluation and simulations for the proposed facility location model are presented in the case of real road networks corresponding to the cities of Boston and Dublin.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.03.014
      Issue No: Vol. 96 (2018)
       
  • An interactive approximation algorithm for multi-objective integer
           programs
    • Authors: Banu Lokman; Murat Köksalan; Pekka J. Korhonen; Jyrki Wallenius
      Pages: 80 - 90
      Abstract: Publication date: August 2018
      Source:Computers & Operations Research, Volume 96
      Author(s): Banu Lokman, Murat Köksalan, Pekka J. Korhonen, Jyrki Wallenius
      We develop an interactive algorithm that approximates the most preferred solution for any multi-objective integer program with a desired level of accuracy, provided that the decision maker's (DM's) preferences are consistent with a nondecreasing quasiconcave value function. Using pairwise comparisons of the DM, we construct convex cones and eliminate the inferior regions that are close to being dominated by the cones in addition to the regions dominated by the cones. The algorithm allows the DM to change the desired level of accuracy during the solution process. We test the performance of the algorithm on a set of multi-objective combinatorial optimization problems. It performs very well in terms of the quality of the solution found, the solution time, and the required preference information.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.04.005
      Issue No: Vol. 96 (2018)
       
  • Convex preference cone-based approach for many objective optimization
           problems
    • Authors: Ankur Sinha; Pekka Malo; Markku Kallio
      Pages: 1 - 11
      Abstract: Publication date: July 2018
      Source:Computers & Operations Research, Volume 95
      Author(s): Ankur Sinha, Pekka Malo, Markku Kallio
      Many objective optimization problems have turned out to be a considerable challenge for evolutionary algorithms due to the difficulty of finding and visualizing high-dimensional Pareto frontiers. Fortunately, however, the task can be simplified whenever an interaction with a human decision maker is possible. Instead of finding the entire Pareto frontier, the evolutionary search can be guided to the parts of the space that are most relevant for the decision maker. In this paper, we propose an interactive method for solving many objective optimization problems. Drawing on the recent developments in multiple criteria decision making, we introduce an effective strategy for leveraging polyhedral preference cones within an evolutionary algorithm. The approach is mathematically motivated and is applicable to situations, where the user’s preferences can be assumed to follow an unknown quasi-concave and increasing utility function. In addition to considering the preference cones as a tool for eliminating non-preferred solution candidates, we also present how the the cones can be leveraged in approximating the directions of steepest ascent to guide the subsequent search done by the evolutionary algorithm through a proposed merit function. To evaluate the performance of the algorithm, we consider well known test problems as well as a practical facility location problem.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.02.015
      Issue No: Vol. 95 (2018)
       
  • An exact algorithm for the unrestricted block relocation problem
    • Authors: Shunji Tanaka; Fumitaka Mizuno
      Pages: 12 - 31
      Abstract: Publication date: July 2018
      Source:Computers & Operations Research, Volume 95
      Author(s): Shunji Tanaka, Fumitaka Mizuno
      The purpose of this study is to propose an exact algorithm for the unrestricted block relocation problem with distinct priorities. In this problem, a storage area is considered where blocks of the same size are stacked vertically in tiers. Because we can access only topmost blocks, relocations of blocks are required when other blocks are retrieved. The objective is to minimize the total number of such relocations necessary for retrieving all the blocks one by one according to a specified order. In the restricted version of this problem, only the topmost block above the target block is relocatable. On the other hand, no such restriction is imposed on the unrestricted problem, which is considered in this study. We also assume that each block is assigned a distinct retrieval priority and the retrieval order of blocks is unique. To improve the efficiency of a branch-and-bound algorithm for this problem, we propose several dominance properties to eliminate unnecessary nodes in the search tree. Furthermore, we propose a new lower bound of the total number of relocations. The effectiveness of the proposed exact algorithm is verified by numerical experiments for benchmark instances in the literature.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.02.019
      Issue No: Vol. 95 (2018)
       
  • Testing probabilistic models of choice using column generation
    • Authors: Bart Smeulders; Clintin Davis-Stober; Michel Regenwetter; Frits C.R. Spieksma
      Pages: 32 - 43
      Abstract: Publication date: July 2018
      Source:Computers & Operations Research, Volume 95
      Author(s): Bart Smeulders, Clintin Davis-Stober, Michel Regenwetter, Frits C.R. Spieksma
      In so-called random preference models of probabilistic choice, a decision maker chooses according to an unspecified probability distribution over preference states. The most prominent case arises when preference states are linear orders or weak orders of the choice alternatives. The literature has documented that actually evaluating whether decision makers’ observed choices are consistent with such a probabilistic model of choice poses computational difficulties. This severely limits the possible scale of empirical work in behavioral economics and related disciplines. We propose a family of column generation based algorithms for performing such tests. We evaluate our algorithms on various sets of instances. We observe substantial improvements in computation time and conclude that we can efficiently test substantially larger data sets than previously possible.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.03.001
      Issue No: Vol. 95 (2018)
       
  • p-hub median problem for non-complete networks
    • Authors: İbrahim Akgün; Barbaros Ç Tansel
      Pages: 56 - 72
      Abstract: Publication date: July 2018
      Source:Computers & Operations Research, Volume 95
      Author(s): İbrahim Akgün, Barbaros Ç Tansel
      Most hub location studies in the literature use a complete-network structure as an input in developing optimization models. This starting point is not necessarily from assuming that the underlying real-world network (e.g., physical network such as road and rail networks) on which the hub system will operate is complete. It is implicitly or explicitly assumed that a complete-network structure is constructed from the shortest-path lengths between origin-destination pairs on the underlying real-world network through a shortest-path algorithm. Thus, the network structure used as an input in most models is a complete network with the distances satisfying the triangle inequality. Even though this approach has gained acceptance, not using the real-world network and its associated data structure directly in the models may result in several computational and modeling disadvantages. More importantly, there are cases in which the shortest path is not preferred or the triangle inequality is not satisfied. In this regard, we take a new direction and define the p-hub median problem directly on non-complete networks that are representative of many real-world networks. The proposed problem setting and the modeling approach allow several basic assumptions about hub location problems to be relaxed and provides flexibility in modeling several characteristics of real-life hub networks. The proposed models do not require any specific cost and network structure and allow to use the real-world network and its asociated data structure directly. The models can be used with the complete networks as well. We also develop a heuristic based on the proposed modeling aproach and present computational studies.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.02.014
      Issue No: Vol. 95 (2018)
       
  • Exact method for the capacitated competitive facility location problem
    • Authors: Vladimir Beresnev; Andrey Melnikov
      Pages: 73 - 82
      Abstract: Publication date: July 2018
      Source:Computers & Operations Research, Volume 95
      Author(s): Vladimir Beresnev, Andrey Melnikov
      We consider a competition between two parties maximizing their profit from servicing customers. A decision making process is assumed to be organized in a Stackelberg game framework. In the model, we are given with two finite sets: a set of customers and a set of potential facilities’ locations. The parties, called the Leader and the Follower, sequentially open their facilities in some of the potential locations. A party opening the most preferable facility for a customer captures him or her. Facilities’ capacities are assumed to be finite, and the problem is to decide where to open facilities and how to assign them to service captured customers provided that capacity constraints are satisfied. The Leader’s problem is formalized as an optimistic bi-level mixed-integer program. We show that it can be considered as a problem to maximize a pseudo-Boolean function depending on a “small” number of Boolean variables. To find an optimal solution of this problem, we suggest a branch-and-bound algorithm where an estimating problem in a form of mixed-integer programming is utilized to calculate an upper bound for values of the objective function. In computational experiments, we study the quality of the upper bound and the performance of the method on randomly generated inputs.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.02.013
      Issue No: Vol. 95 (2018)
       
  • A mixed-integer programming approach for locating jamming devices in a
           flow-jamming attack
    • Authors: Satish Vadlamani; David Schweitzer; Hugh Medal; Apurba Nandi; Burak Eksioglu
      Pages: 83 - 96
      Abstract: Publication date: July 2018
      Source:Computers & Operations Research, Volume 95
      Author(s): Satish Vadlamani, David Schweitzer, Hugh Medal, Apurba Nandi, Burak Eksioglu
      The ubiquitous nature of wireless networks makes them increasingly prone to jamming attacks as such attacks become more sophisticated. In this paper, we seek to gain understanding about a particular type of jamming attack: the flow-jamming attack. Toward this end, we provide a mixed-integer programming model for optimizing the location of jamming devices for flow-jamming attacks. An accelerated Benders’ decomposition approach was used to solve the model. We solved the problem for two realistic networks and 18 randomly generated networks and found that the Benders’ approach was computationally faster than CPLEX for nearly all the problem instances, particularly for larger problems with 1440 binary variables. The experimental results show that optimally locating jamming devices can increase the impact of flow-jamming attacks. Specifically, as the number of possible locations increases the jammers’ efficacy increases as well, but there is a clear point of diminishing returns. Also, adding lower-powered jammers to work in conjunction with higher powered jammers significantly increases overall efficacy in spite of the power difference.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.02.020
      Issue No: Vol. 95 (2018)
       
  • Matheuristic approaches for parallel machine scheduling problem with
           time-dependent deterioration and multiple rate-modifying activities
    • Authors: Young-Bin Woo; Byung Soo Kim
      Pages: 97 - 112
      Abstract: Publication date: July 2018
      Source:Computers & Operations Research, Volume 95
      Author(s): Young-Bin Woo, Byung Soo Kim
      The study considers a parallel machine scheduling (PMS) problem with time-dependent deterioration and multiple rate-modifying activities (RMAs). The objective of the problem is to simultaneously determine the number and positions of RMAs and a schedule of jobs on parallel machines to minimize the makespan. In order to determine an optimal solution, a mixed integer linear programming (MILP) model for the PMS problem is introduced. Subsequently, novel metaheuristic algorithms embedding a mathematical model are developed based on matheuristic approaches to effectively handle large-sized problems. The matheuristic approaches decompose the original problem into sub-problems by determining partial decision variables from each iteration in simulated annealing (SA) and genetic algorithm (GA). Subsequently, the rest of the decision variables are optimally determined by using a mathematical model for the sub-problems with partial decision variables predetermined. In order to enhance the performance of SA and GA, an adjustment heuristic is proposed based on an optimality property for the problem. The performance of the proposed algorithms is evaluated by conducting numerical experiments based on randomly generated examples, and subsequently the behavior of the algorithms is discussed.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.02.017
      Issue No: Vol. 95 (2018)
       
  • A matheuristic for the two-stage fixed-charge transportation problem
    • Authors: Herminia I. Calvete; Carmen Galé; José A. Iranzo; Paolo Toth
      Pages: 113 - 122
      Abstract: Publication date: July 2018
      Source:Computers & Operations Research, Volume 95
      Author(s): Herminia I. Calvete, Carmen Galé, José A. Iranzo, Paolo Toth
      This paper addresses the two-stage fixed-charge transportation problem which involves the distribution of a commodity from plants to customers through intermediate depots, while minimizing the overall costs incurred. There are two costs associated with each arc: a fixed cost for the use of the arc, and a variable cost proportional to the number of units sent along the arc. First, we prove some theoretical properties which extend well-known results of the fixed-charge transportation problem. Then, we present a matheuristic that uses an evolutionary algorithm and exploits these properties to guide the algorithm towards better solutions. The chromosome of the evolutionary algorithm controls the arcs that can be used in the delivery. Its fitness is computed as the objective function value of a feasible solution of the problem, which is obtained by applying optimization techniques. The computational results show the effectiveness of the algorithm.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.03.007
      Issue No: Vol. 95 (2018)
       
  • Timetable rearrangement to cope with railway maintenance activities
    • Authors: Diego Arenas; Paola Pellegrini; Saïd Hanafi; Joaquin Rodriguez
      Pages: 123 - 138
      Abstract: Publication date: July 2018
      Source:Computers & Operations Research, Volume 95
      Author(s): Diego Arenas, Paola Pellegrini, Saïd Hanafi, Joaquin Rodriguez
      Maintenance activities on the railway infrastructure are necessary to maintain its functionality and availability. Commonly, the maintenance activities are planned first. Then, the timetable is elaborated respecting the unavailability periods caused by the former. However, sometimes unplanned maintenance activities have to be introduced at short notice, and the timetable must be rearranged to respect the new unavailabilities. In addition, specific trains may be necessary to perform maintenance activities, and they are typically not scheduled in the timetable. In this case, the timetable may need to be further rearranged to integrate the maintenance trains. In this paper, we propose a mixed-integer linear programming formulation that rearranges a timetable to cope with the capacity consumption produced by maintenance activities. It includes the consideration of maintenance trains and other specific constraints, such as temporary speed limitations. In this formulation, the rearrangement of the timetable is optimized based on a microscopic representation of both the infrastructure and the rolling stock. We assess three algorithms founded on this formulation on a real case study in the French railway network and we show their practical applicability.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.02.018
      Issue No: Vol. 95 (2018)
       
  • Picker routing in rectangular mixed shelves warehouses
    • Authors: Felix Weidinger
      Pages: 139 - 150
      Abstract: Publication date: July 2018
      Source:Computers & Operations Research, Volume 95
      Author(s): Felix Weidinger
      Scattered storage (also denoted as mixed shelves storage) is a warehousing strategy often found in business-to-consumer online retailing. Unit loads are broken down into single items that are spread throughout the warehouse, leading to multiple storage positions per stock keeping unit. This paper investigates the picker routing problem in a rectangular scattered storage warehouse, which differs from classical picker routing problems by being a combined selection and routing problem. A proof of NP-hardness in the strong sense is provided and suited solution procedures are presented. Additionally, the impact of the degree of scatter on the length of picking tours is investigated for differing levels of heterogeneity of the order lines, providing managerial insights on when scattered storage should or should not be applied.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.03.012
      Issue No: Vol. 95 (2018)
       
  • An extensive operations and maintenance planning problem with an efficient
           solution method
    • Authors: Javad Seif; Andrew J. Yu
      Pages: 151 - 162
      Abstract: Publication date: July 2018
      Source:Computers & Operations Research, Volume 95
      Author(s): Javad Seif, Andrew J. Yu
      In this paper, we extend the formulation and solution algorithm of a Flight and Maintenance Planning (FMP) problem to cover a wider range of applications. We consider a general Operations and Maintenance Planning (OMP) case where machines are shared between multiple operation schedules as well as have multiple preventive maintenance activities. In this case, machines have different usage-based intervals and the maintenance duration varies for each machine. We formulate and optimize the OMP problem to accommodate the maintenance requirements and physical characteristics of multiple stations. We evaluate the performance of the generalized solution methodology and show its effectiveness and efficiency through computational experiments.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.03.010
      Issue No: Vol. 95 (2018)
       
  • Novel integer linear programming models for the facility layout problem
           with fixed-size rectangular departments
    • Authors: Jianguang Feng; Ada Che
      Pages: 163 - 171
      Abstract: Publication date: July 2018
      Source:Computers & Operations Research, Volume 95
      Author(s): Jianguang Feng, Ada Che
      This paper considers the facility layout problem (FLP) that places a set of fixed-size rectangular departments on a given rectangular site in such a way that the total material flow between adjacent departments is maximized. We demonstrate that an existing integer linear programming (ILP) model for this problem is flawed. Then, two novel ILP models are developed by reformulating some constraints of the existing model from different perspectives. They both significantly reduce the quantity of decision variables. It is also shown that the proposed models can be simplified if all departments have the same size. Numerical experiments conducted on several benchmark instances show that the proposed models outperform the existing one with promising results. Our models can solve all tested instances to optimality within reasonable time, while the existing one cannot.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.03.013
      Issue No: Vol. 95 (2018)
       
  • Locating hyperplanes to fitting set of points: A general framework
    • Authors: Víctor Blanco; Justo Puerto; Román Salmerón
      Pages: 172 - 193
      Abstract: Publication date: July 2018
      Source:Computers & Operations Research, Volume 95
      Author(s): Víctor Blanco, Justo Puerto, Román Salmerón
      This paper presents a family of methods for locating/fitting hyperplanes with respect to a given set of points. We introduce a general framework for a family of aggregation criteria, based on ordered weighted operators, of different distance-based errors. The most popular methods found in the specialized literature, namely least sum of squares, least absolute deviation, least quantile of squares or least trimmed sum of squares among many others, can be cast within this family as particular choices of the errors and the aggregation criteria. Unified mathematical programming formulations for these methods are provided and some interesting cases are analyzed. The most general setting give rise to mixed integer nonlinear programming problems. For those situations we present inner and outer linear approximations to assess tractable solution procedures. It is also proposed a new goodness of fitting index which extends the classical coefficient of determination and allows one to compare different fitting hyperplanes. A series of illustrative examples and extensive computational experiments implemented in R are provided to show the applicability of the proposed methods.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.03.009
      Issue No: Vol. 95 (2018)
       
  • An Efficient Implementation of a Static Move Descriptor-based Local Search
           Heuristic
    • Authors: Onne Beek; Birger Raa; Wout Dullaert; Daniele Vigo
      Pages: 1 - 10
      Abstract: Publication date: June 2018
      Source:Computers & Operations Research, Volume 94
      Author(s): Onne Beek, Birger Raa, Wout Dullaert, Daniele Vigo
      This paper proposes several strategies for a more efficient implementation of the concept of Static Move Descriptors (SMDs), a recently developed technique that significantly speeds up Local Search-based algorithms. SMDs exploit the fact that each local search step affects only a small part of the solution and allow for efficient tracking of changes at each iteration, such that unnecessary reevaluations can be avoided. The concept is highly effective at reducing computation times and is sufficiently generic to be applied in any Local Search-based algorithm. Despite its significant advantages, the design proposed in the literature suffers from high overhead and high implementational complexity. Our proposals lead to a much leaner and simpler implementation that offers better extendibility and significant further speedups of local search algorithms. We compare implementations for the Capacitated Vehicle Routing Problem (CVRP) - a well-studied, complex problem that serves as a benchmark for a wide variety of optimization techniques.

      PubDate: 2018-02-26T00:11:09Z
      DOI: 10.1016/j.cor.2018.01.006
      Issue No: Vol. 94 (2018)
       
  • Redundancy system design for an aircraft door management system
    • Authors: Lukas Schäfer; Sergio García; Andreas Mitschke; Vassili Srithammavanh
      Pages: 11 - 22
      Abstract: Publication date: June 2018
      Source:Computers & Operations Research, Volume 94
      Author(s): Lukas Schäfer, Sergio García, Andreas Mitschke, Vassili Srithammavanh
      The door management system (DMS) is a safety-critical system in an aircraft which checks if all doors are properly closed and the cabin has the correct pressure. As for every safety-critical system in an aircraft, it has to meet some safety regulations and it should be designed optimally in terms of weight, cost or power consumption. This paper studies the problem of designing a DMS optimally as per the previous objectives while guaranteeing that the system is k-redundant. We call this new problem the DMS design problem with redundancy. First, we propose a new MILP model for the DMS problem which includes redundancy. Because the model is too difficult to be solved efficiently by standard MILP solvers, we introduce specialized branching rules and a new heuristic. Computational tests are run for example instances of the DMS problem by implementing these new rule in CPLEX. It is shown that the solving time is significantly reduced through the new branching rules and heuristic.

      PubDate: 2018-02-26T00:11:09Z
      DOI: 10.1016/j.cor.2018.02.005
      Issue No: Vol. 94 (2018)
       
  • Stochastic lot sizing problem with nervousness considerations
    • Authors: E. Koca; H. Yaman; M.S. Aktürk
      Pages: 23 - 37
      Abstract: Publication date: June 2018
      Source:Computers & Operations Research, Volume 94
      Author(s): E. Koca, H. Yaman, M.S. Aktürk
      In this paper, we consider the multistage stochastic lot sizing problem with controllable processing times under nervousness considerations. We assume that the processing times can be reduced in return for extra cost (compression cost). We generalize the static and static-dynamic uncertainty strategies to eliminate setup oriented nervousness and control quantity oriented nervousness. We restrict the quantity oriented nervousness by introducing a new concept called promised production amounts, and considering new range constraints and a nervousness cost function. We formulate the problem as a second-order cone mixed integer program (SOCMIP), and apply the conic strengthening. We observe the continuous mixing set substructure in our formulation that arises due the controllable processing times. We reformulate the problem by using an extended formulation for the continuous mixing set and solve the problem by a branch-and-cut approach. The computational experiments indicate that the reformulation reduces the root gaps and this helps to solve the problem in less computation times. Moreover, in our computational experiments we investigate the impact of new restrictions, specifically the additional cost of eliminating the setup oriented nervousness, on the total costs and the system nervousness. Our computational results clearly indicate that we could significantly reduce the nervousness costs and generate more stable production schedules with a relatively small increase in the total cost.

      PubDate: 2018-02-26T00:11:09Z
      DOI: 10.1016/j.cor.2018.01.021
      Issue No: Vol. 94 (2018)
       
  • Exact algorithms for bi-objective ring tree problems with reliability
           measures
    • Authors: Alessandro Hill; Silvia Schwarze
      Pages: 38 - 51
      Abstract: Publication date: June 2018
      Source:Computers & Operations Research, Volume 94
      Author(s): Alessandro Hill, Silvia Schwarze
      We introduce bi-objective models for ring tree network design with a focus on network reliability within telecommunication applications. Our approaches generalize the capacitated ring tree problem (CRTP) which asks for a partially reliable topology that connects customers with different security requirements to a depot node by combined ring and tree graphs. While the CRTP aims at optimizing the edge installation costs, we propose four alternative, reliability-oriented objective functions. We study the case of service interruptions due to single-edge failures, and consider the overall number of tree customers and tree edges, the maximal number of subtree customers, and the maximal number of tree hops from rings as additional measures. To model the corresponding novel bi-objective problems, we develop mathematical multi-commodity flow formulations and identify relationships between the new objectives. For identifying the Pareto fronts, we apply an ϵ-constraint method based on integer programming. The computational efficiency is increased by employing local search heuristics in order to tighten upper bounds and by valid inequalities to strengthen lower bounds in the subproblems. In a computational study we report results, illustrate solution network topologies and extensively analyze the algorithm performance for instances from the literature.

      PubDate: 2018-02-26T00:11:09Z
      DOI: 10.1016/j.cor.2018.02.004
      Issue No: Vol. 94 (2018)
       
  • The periodic supply vessel planning problem with flexible departure times
           and coupled vessels
    • Authors: Yauheni Kisialiou; Irina Gribkovskaia; Gilbert Laporte
      Pages: 52 - 64
      Abstract: Publication date: June 2018
      Source:Computers & Operations Research, Volume 94
      Author(s): Yauheni Kisialiou, Irina Gribkovskaia, Gilbert Laporte
      In upstream offshore petroleum logistics, periodic supply vessel planning plays an important role since it ensures the replenishment of offshore installations on a regular basis with all the necessary equipment and materials from an onshore base. The problem involves the determination of the fleet composition and of the vessel schedules over a given time horizon. We present an extended version of this problem involving flexible departures from the base and the possibility of coupling vessels by swapping their schedules. We propose a voyage-based model that can be solved exactly for small- and medium-size instances. For the solution of larger instances, we have developed an adaptive large neighborhood heuristic, which yields optimal or near-optimal solutions relatively fast on small- and medium- size instances. Its performance on larger instances is significantly better than that of alternative algorithms previously developed for the same problem.

      PubDate: 2018-02-26T00:11:09Z
      DOI: 10.1016/j.cor.2018.02.008
      Issue No: Vol. 94 (2018)
       
  • Service System Design with Immobile Servers, Stochastic Demand and
           Concave-Cost Capacity Selection
    • Authors: Samir Elhedhli; Yan Wang; Ahmed Saif
      Pages: 65 - 75
      Abstract: Publication date: Available online 3 February 2018
      Source:Computers & Operations Research
      Author(s): Samir Elhedhli, Yan Wang, Ahmed Saif
      The service system design problem is a location-allocation problem with service quality considerations that is often modeled as a network of M/M/1 queues to minimize facility setup, customer access, and waiting costs. Traditionally, capacity decisions are either ignored or modeled as a selection among discrete capacity levels. In this work, we study the general continuous capacity case and account for economies-of-scale in its cost through an increasing concave function. We focus on the special square-root case that has been shown to model capacity in terms of the number of servers needed under Poisson arrivals and exponential service times. The problem is formulated as a mixed-integer nonlinear program with concave and convex terms in the objective function. Two novel resolution approaches are proposed: In the first, the problem is reformulated as a mixed-integer quadratic program with fourth-degree polynomial equality constraints. These constraints and the quadratic objective function are approximated using piecewise-linear segments. In the second, we use Lagrangian relaxation to decompose the problem and reformulate the subproblems as second-order cone programs that are solved at multiple utilization levels. The Lagrangian multipliers are updated using a cutting-plane method and a feasible solution is obtained by solving the corresponding set-covering formulation. The solution approaches are tested and compared. The linearization approach provides high quality solutions within short computational times for small instances and lower accuracy; whereas the Lagrangian approach scales well as size increases.

      PubDate: 2018-02-04T23:05:50Z
      DOI: 10.1016/j.cor.2018.01.019
      Issue No: Vol. 94 (2018)
       
  • A Comparison of Formulations and Relaxations for Cross-dock Door
           Assignment Problems
    • Authors: W. Nassief; I. Contreras; B. Jaumard
      Pages: 76 - 88
      Abstract: Publication date: Available online 2 February 2018
      Source:Computers & Operations Research
      Author(s): W. Nassief, I. Contreras, B. Jaumard
      This paper deals with cross-dock door assignment problems in which the assignments of incoming trucks to strip doors, and outgoing trucks to stack doors are determined, with the objective of minimizing the total handling cost. We present two new mixed integer programming formulations which are theoretically and computationally compared with existing ones. One of such requires a column generation algorithm to solve its associated linear relaxation. We present the results of a series of computational experiments to evaluate the performance of the formulations on a set of benchmark instances. We also perform sensitivity analysis with respect to several input parameters of the Cross-dock Door Assignment Problems.

      PubDate: 2018-02-04T23:05:50Z
      DOI: 10.1016/j.cor.2018.01.022
      Issue No: Vol. 94 (2018)
       
  • A hybrid discrete teaching-learning based meta-heuristic for solving
           no-idle flow shop scheduling problem with total tardiness criterion
    • Authors: Weishi Shao; Dechang Pi; Zhongshi Shao
      Pages: 89 - 105
      Abstract: Publication date: June 2018
      Source:Computers & Operations Research, Volume 94
      Author(s): Weishi Shao, Dechang Pi, Zhongshi Shao
      This paper proposes a hybrid discrete teaching-learning based meta-heuristic (HDTLM) to solve the no-idle flow shop scheduling problem (NIFSP) with the total tardiness criterion. To imitate the teaching-learning phenomenon in the real world, the HDTLM is composed of three phases, i.e. discrete teaching phase based on probabilistic model, discrete learning phase based on hierarchical structure, and reinforcement learning. In the discrete teaching phase, a probabilistic model based on the elite learners and the best learner is used to generate a series of position sequences, and the concept of consensus permutation is employed to replace the mean individual in the teaching-learning based optimization (TLBO) algorithm. Each job of the consensus permutation is inserted into a new sequence according to the position sequence. In the discrete learning phase, according to different levels of learners, all learners are divided into three layers, i.e. top layer, middle layer, bottom layer, and then the proposed learning phase adopts the order of top-down to spread the knowledge. The reinforcement learning phase is applied to the best learner to further improve the knowledge level of teacher. The parameters of the HDTLM are calibrated by a design of experiments (DOE) on randomly generated testing instances. The computational results on Taillard and Ruiz's benchmark sets and statistical analyses show that the HDTLM is an efficient and effective method for solving the NIFSP.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.02.003
      Issue No: Vol. 94 (2018)
       
  • Packing unequal rectangles and squares in a fixed size circular container
           using formulation space search
    • Authors: C.O. López; J.E. Beasley
      Pages: 106 - 117
      Abstract: Publication date: June 2018
      Source:Computers & Operations Research, Volume 94
      Author(s): C.O. López, J.E. Beasley
      In this paper we formulate the problem of packing unequal rectangles/squares into a fixed size circular container as a mixed-integer nonlinear program. Here we pack rectangles so as to maximise some objective (e.g. maximise the number of rectangles packed or maximise the total area of the rectangles packed). We show how we can eliminate a nonlinear maximisation term that arises in one of the constraints in our formulation. We indicate the amendments that can be made to the formulation for the special case where we are maximising the number of squares packed. A formulation space search heuristic is presented and computational results given for publicly available test problems involving up to 30 rectangles/squares. Our heuristic deals with the case where the rectangles are of fixed orientation (so cannot be rotated) and with the case where the rectangles can be rotated through ninety degrees.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.02.012
      Issue No: Vol. 94 (2018)
       
  • A cellular memetic algorithm for the examination timetabling problem
    • Authors: Nuno Leite; Carlos M. Fernandes; Fernando Melício; Agostinho C. Rosa
      Pages: 118 - 138
      Abstract: Publication date: June 2018
      Source:Computers & Operations Research, Volume 94
      Author(s): Nuno Leite, Carlos M. Fernandes, Fernando Melício, Agostinho C. Rosa
      The timetabling problem involves the scheduling of a set of entities (e.g., lectures, exams, vehicles, or people) to a given set of resources in a limited number of time slots, while satisfying a set of constraints. In this paper, a cellular memetic algorithm is proposed for solving the examination timetabling problem. Cellular evolutionary algorithms are population-based metaheuristics. They differ from non-cellular algorithms in that the population is organised in a cellular structure, providing for a smooth actualisation of the populations that contributes to improving the population diversity. The proposed cellular evolutionary algorithm is hybridised with the threshold acceptance local search metaheuristic. The implemented algorithm uses feasible genetic recombination and local search operators, thus limiting the exploration to the feasible solution space. The effect of the threshold acceptance used in the hybrid algorithm for the examination timetabling problem is studied. It is shown that a low threshold decreasing rate is needed in order to rearrange the most difficult exams in better periods, allowing for the easy set of exams to be placed in good periods as well. The approach was tested on the public Toronto and ITC 2007 benchmark sets. The proposed hybrid is able to attain four and three new upper bounds for the Toronto and ITC 2007 benchmark sets, respectively.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.02.009
      Issue No: Vol. 94 (2018)
       
  • Robust vehicle routing problem with hard time windows under demand and
           travel time uncertainty
    • Authors: C. Hu; J. Lu; X. Liu; G. Zhang
      Pages: 139 - 153
      Abstract: Publication date: June 2018
      Source:Computers & Operations Research, Volume 94
      Author(s): C. Hu, J. Lu, X. Liu, G. Zhang
      Due to an increase in customer-oriented service strategies designed to meet more complex and exacting customer requirements, meeting a scheduled time window has become an important part of designing vehicle routes for logistics activities. However, practically, the uncertainty in travel times and customer demand often means vehicles miss these time windows, increasing service costs and decreasing customer satisfaction. In an effort to find a solution that meets the needs of real-world logistics, we examine the vehicle routing problem with hard time windows under demand and travel time uncertainty. To address the problem, we build a robust optimization model based on novel route-dependent uncertainty sets. However, due to the complex nature of the problem, the robust model is only able to tackle small-sized instances using standard solvers. Therefore, to tackle large instances, we design a two-stage algorithm based on a modified adaptive variable neighborhood search heuristic. The first stage of the algorithm minimizes the total number of vehicle routes, while the second stage minimizes the total travel distance. Extensive computational experiments are conducted with modified versions of Solomon’s benchmark instances. The numerical results show that the proposed two-stage algorithm is able to find optimal solutions for small-sized instances and good-quality robust solutions for large-sized instances with little increase to the total travel distance and/or the number of vehicles used. A detailed analysis of the results also reveals several managerial insights for decision-makers in the logistics industry.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.02.006
      Issue No: Vol. 94 (2018)
       
  • A sustainable aggregate production planning model for the chemical process
           industry
    • Authors: Gerd J. Hahn; Marcus Brandenburg
      Pages: 154 - 168
      Abstract: Publication date: June 2018
      Source:Computers & Operations Research, Volume 94
      Author(s): Gerd J. Hahn, Marcus Brandenburg
      Process industries typically involve complex manufacturing operations and thus require adequate decision support for aggregate production planning (APP). In this paper, we focus on two relevant features of APP in process industry operations: (i) sustainable operations planning involving multiple alternative production modes/routings with specific production-related carbon emission and the social dimension of varying operating rates, (ii) integrated campaign planning with the operational level in order to anticipate production mix/volume/routing decisions on campaign lead times and WIP inventories as well as the impact of variability originating from a stochastic manufacturing environment. We focus on the issue of multi-level chemical production processes and highlight the mutual trade-offs along the triple bottom line concerning economic, environmental and social factors. To this end, production-related carbon emission and overtime working hours are considered as externalized factors as well as internalized ones in terms of resulting costs. A hierarchical decision support tool is presented that combines a deterministic linear programming model and an aggregate stochastic queuing network model. The approach is exemplified at a case example from the chemical industry to illustrate managerial insights and methodological benefits of our approach.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2017.12.011
      Issue No: Vol. 94 (2018)
       
  • Formulations and algorithms for the Pickup and Delivery Traveling Salesman
           Problem with Multiple Stacks
    • Authors: Armando H. Pereira; Sebastián Urrutia
      Pages: 1 - 14
      Abstract: Publication date: May 2018
      Source:Computers & Operations Research, Volume 93
      Author(s): Armando H. Pereira, Sebastián Urrutia
      In the Pickup and Delivery Traveling Salesman Problem with Multiple Stacks, one vehicle must fulfill a set of pickup and delivery requests. While being transported, items are stored in stacks with limited capacity. Each stack must follow the Last-In-First-Out policy. The objective of the problem is to find a vehicle route that fulfills all requests and minimizes traveled distance. In this paper, we propose new integer programming formulations to the problem along with ad hoc branch-and-cut algorithms and valid inequalities. The formulations and algorithms are applied to benchmark instances and the computational results are compared with the literature. Instances for which an optimal solution was previously known in the literature are solved more efficiently in this work. Also, new optimality certificates are provided for seven instances.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.01.005
      Issue No: Vol. 93 (2018)
       
  • A choice function hyper-heuristic framework for the allocation of
           maintenance tasks in Danish railways
    • Authors: Shahrzad M. Pour; John H. Drake; Edmund K. Burke
      Pages: 15 - 26
      Abstract: Publication date: May 2018
      Source:Computers & Operations Research, Volume 93
      Author(s): Shahrzad M. Pour, John H. Drake, Edmund K. Burke
      A new signalling system in Denmark aims at ensuring fast and reliable train operations. However, it imposes very strict time limits on recovery plans in the event of failure. As a result, it is necessary to develop a new approach to the entire maintenance scheduling process. In the largest region of Denmark, the Jutland peninsula, there is a decentralised structure for maintenance planning where the crew start their duties from their home locations rather than starting from a single depot. In this paper, we allocate a set of maintenance tasks in Jutland to a set of maintenance crew members, defining the sub-region that each crew member is responsible for. Two key considerations must be made when allocating tasks to crew members. Firstly a fair balance of workload must exist between crew members. Secondly, the distance between two tasks in the same sub-region must be minimised in order to facilitate a quick response in the case of unexpected failure. We propose a perturbative selection hyper-heuristic framework to improve initial solutions by reassigning outliers (those tasks that are far away) to another crew member at each iteration, using one of five low-level heuristics. The results from two hyper-heuristics, using a number of different initial solution construction methods are presented over a set of 12 benchmark problem instances.

      PubDate: 2018-02-04T23:05:50Z
      DOI: 10.1016/j.cor.2017.09.011
      Issue No: Vol. 93 (2018)
       
  • The robust (minmax regret) assembly line worker assignment and balancing
           problem
    • Authors: Jordi Pereira
      Pages: 27 - 40
      Abstract: Publication date: May 2018
      Source:Computers & Operations Research, Volume 93
      Author(s): Jordi Pereira
      Line balancing aims to assign the assembly tasks to the stations that compose the assembly line. A recent body of literature has been devoted to heterogeneity in the assembly process introduced by different workers. In such an environment, task times depend on the worker performing the operation and the problem aims at assigning tasks and workers to stations in order to maximize the throughput of the line. In this work, we consider an interval data version of the assembly line worker assignment and balancing problem (ALWABP) in which it is assumed that lower and upper bounds for the task times are known, and the objective is to find an assignment of tasks and workers to the workstations such that the absolute maximum regret among all of the possible scenarios is minimized. The relationship with other interval data minmax regret (IDMR) problems is investigated, the inapplicability of previous approximation methods is studied, regret evaluation is considered, and exact and heuristic solution methods are proposed and analyzed. The results of the proposed methods are compared in a computational experiment, showing the applicability of the method and the theoretical results to solve the problem under study. Additionally, these results are not only applicable to the problem in hand, but also to a more general class of problems.

      PubDate: 2018-02-04T23:05:50Z
      DOI: 10.1016/j.cor.2018.01.009
      Issue No: Vol. 93 (2018)
       
  • Customized multi-period stochastic assignment problem for social
           engagement and opportunistic IoT
    • Authors: Edoardo Fadda; Guido Perboli; Roberto Tadei
      Pages: 41 - 50
      Abstract: Publication date: May 2018
      Source:Computers & Operations Research, Volume 93
      Author(s): Edoardo Fadda, Guido Perboli, Roberto Tadei
      An enormous number of devices are currently available to collect data. One of the main applications of these devices is in the urban environment, where they can collect data useful for improving the operations management and reducing economic, environmental and social costs. This is the main goal of smart cities. To gather these data from devices, companies can build expensive networks able of reaching every part of the city or they can use cheaper alternatives as opportunistic connections, i.e., use the devices of selected people (e.g., mobile users) as mobile hotspots in exchange for a reward. In this paper, we consider this second choice and, in particular, we solve the problem of minimizing the sum of the rewards while providing the connectivity to all sensors. We show that the stochastic approach must be considered since deterministic solutions produce considerable waste. Finally, to reduce the computational time we apply the loss of reduced costs-based variable fixing (LRCVF) heuristic and we compare, by means of computational tests, the performances of the heuristic and a commercial solver. The results prove the effectiveness of the LRCVF heuristic.

      PubDate: 2018-02-04T23:05:50Z
      DOI: 10.1016/j.cor.2018.01.010
      Issue No: Vol. 93 (2018)
       
  • An effective heuristic algorithm for the partial shop scheduling problem
    • Authors: Tadeu K. Zubaran; Marcus Ritt
      Pages: 51 - 65
      Abstract: Publication date: May 2018
      Source:Computers & Operations Research, Volume 93
      Author(s): Tadeu K. Zubaran, Marcus Ritt
      In a partial shop scheduling problem the operations of each job have to respect a partial order, which can be different for each job. We study the problem of finding a solution of minimal makespan in partial shops. This problem generalizes many problems which have been studied independently in the literature, such as the group shop scheduling problem, the mixed shop scheduling problem, and the open shop scheduling problem. In this paper we propose an algorithm which is able to find solutions for the partial shop scheduling problem. In computational experiments we find that the proposed single heuristic can compete with the state-of-the-art heuristics for the partial shop, group shop, mixed shop, and open shop, and in many cases, improves the state of the art. The main contribution of this paper is the demonstration that a single algorithm can solve effectively many special cases of the partial shop without taking into consideration their particular structure. We highlight the contribution of the main novel components of the algorithm, namely the initial solution generator, neighbourhood structure, and the lower bound for new solutions generated by such neighbourhood.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.01.015
      Issue No: Vol. 93 (2018)
       
  • A branch-and-price algorithm for the Minimum Latency Problem
    • Authors: Teobaldo Bulhões; Ruslan Sadykov; Eduardo Uchoa
      Pages: 66 - 78
      Abstract: Publication date: May 2018
      Source:Computers & Operations Research, Volume 93
      Author(s): Teobaldo Bulhões, Ruslan Sadykov, Eduardo Uchoa
      This paper deals with the Minimum Latency Problem (MLP), a variant of the well-known Traveling Salesman Problem in which the objective is to minimize the sum of waiting times of customers. This problem arises in many applications where customer satisfaction is more important than the total time spent by the server. This paper presents a novel branch-and-price algorithm for MLP that strongly relies on new features for the ng-path relaxation, namely: (1) a new labeling algorithm with an enhanced dominance rule named multiple partial label dominance; (2) a generalized definition of ng-sets in terms of arcs, instead of nodes; and (3) a strategy for decreasing ng-set sizes when those sets are being dynamically chosen. Also, other elements of efficient exact algorithms for vehicle routing problems are incorporated into our method, such as reduced cost fixing, dual stabilization, route enumeration and strong branching. Computational experiments over TSPLIB instances are reported, showing that several instances not solved by the current state-of-the-art method can now be solved.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.01.016
      Issue No: Vol. 93 (2018)
       
  • Relaxations and heuristics for the multiple non-linear separable knapsack
           problem
    • Authors: Claudia D’Ambrosio; Silvano Martello; Luca Mencarelli
      Pages: 79 - 89
      Abstract: Publication date: May 2018
      Source:Computers & Operations Research, Volume 93
      Author(s): Claudia D’Ambrosio, Silvano Martello, Luca Mencarelli
      We consider the multiple non-linear knapsack problem with separable non-convex functions. The problem, which can be modeled as a (mixed) integer non-linear program, is extremely difficult to solve in practice. We present a fast heuristic algorithm, based on constructive techniques, surrogate relaxations, and local search improvements. Computational comparisons with exact and heuristic methods for general non-convex mixed integer non-linear programs show that the proposed approach provides good-quality solutions within small computing times.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2017.12.017
      Issue No: Vol. 93 (2018)
       
  • Relaxation heuristics for the set multicover problem with generalized
           upper bound constraints
    • Authors: Shunji Umetani; Masanao Arakawa; Mutsunori Yagiura
      Pages: 90 - 100
      Abstract: Publication date: May 2018
      Source:Computers & Operations Research, Volume 93
      Author(s): Shunji Umetani, Masanao Arakawa, Mutsunori Yagiura
      We consider an extension of the set covering problem (SCP) introducing (i) multicover and (ii) generalized upper bound (GUB) constraints. For the conventional SCP, the pricing method has been introduced to reduce the size of instances, and several efficient heuristic algorithms based on such reduction techniques have been developed to solve large-scale instances. However, GUB constraints often make the pricing method less effective, because they often prevent solutions from containing highly evaluated variables together. To overcome this problem, we develop heuristic algorithms to reduce the size of instances, in which new evaluation schemes of variables are introduced taking account of GUB constraints. We also develop an efficient implementation of a 2-flip neighborhood local search algorithm that reduces the number of candidates in the neighborhood without sacrificing the solution quality. In order to guide the search to visit a wide variety of good solutions, we also introduce a path relinking method that generates new solutions by combining two or more solutions obtained so far. According to computational comparison on benchmark instances, the proposed method succeeds in selecting a small number of promising variables properly and performs quite effectively even for large-scale instances having hard GUB constraints.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.01.007
      Issue No: Vol. 93 (2018)
       
  • SelfSplit parallelization for mixed-integer linear programming
    • Authors: Matteo Fischetti; Michele Monaci; Domenico Salvagnin
      Pages: 101 - 112
      Abstract: Publication date: May 2018
      Source:Computers & Operations Research, Volume 93
      Author(s): Matteo Fischetti, Michele Monaci, Domenico Salvagnin
      SelfSplit is a simple static mechanism to convert a sequential tree-search code into a parallel one. In this paradigm, tree-search is distributed among a set of identical workers, each of which is able to autonomously determine—without any communication with the other workers—the job parts it has to process. SelfSplit already proved quite effective in parallelizing Constraint Programming solvers. In the present paper we investigate the performance of SelfSplit when applied to a Mixed-Integer Linear Programming (MILP) solver. Both ad-hoc and general purpose MILP codes have been considered. Computational results show that SelfSplit, in spite of its simplicity, can achieve good speedups even in the MILP context.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.01.011
      Issue No: Vol. 93 (2018)
       
  • Combined column-and-row-generation for the optimal communication spanning
           tree problem
    • Authors: Christian Tilk; Stefan Irnich
      Pages: 113 - 122
      Abstract: Publication date: May 2018
      Source:Computers & Operations Research, Volume 93
      Author(s): Christian Tilk, Stefan Irnich
      This paper considers the exact solution of the optimal communication spanning tree problem (OCSTP), which can be described as follows: Given an undirected graph with transportation costs on every edge and communication requirements for all pairs of vertices, the OCSTP seeks for a spanning tree that minimizes the sum of the communication costs between all pairs of vertices, where the communication cost of a pair of vertices is defined as their communication requirement multiplied by the transportation cost of the unique tree path that connects the two vertices. Two types of compact formulations for OCSTP were presented in the literature. The first one is a four-index model based on a path formulation. The second one is a three-index model in which a solution is an intersection of spanning trees, each rooted at a different vertex of the graph and modeled using a flow formulation for spanning tree problems. We present Dantzig–Wolfe reformulations for both compact models to be used in a combined column-and-row-generation algorithm. In the path-based reformulation, the pricing problems are simple shortest-path problems, one for each pair of vertices with a positive communication requirement. The pricing problems of the tree-based reformulation are fixed-cost network flow problems, one for each vertex of the graph. We apply different heuristic and exact methods for pricing and present optimal solutions for benchmark instances with up to 50 vertices.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.01.003
      Issue No: Vol. 93 (2018)
       
  • An exact composite lower bound strategy for the resource-constrained
           project scheduling problem
    • Authors: José Coelho; Mario Vanhoucke
      Pages: 135 - 150
      Abstract: Publication date: Available online 2 February 2018
      Source:Computers & Operations Research
      Author(s): José Coelho, Mario Vanhoucke
      This paper reports on results for the well-known resource-constrained project scheduling problem. A branch-and-bound procedure is developed that takes into account all best performing components from literature, varying branching schemes and search strategies, using the best performing dominance rules and assembling these components into a unified search algorithm. A composite lower bound strategy that statically and dynamically selects the best performing bounds from literature is used to find optimal solutions within reasonable times. An extensive computational experiment is set up to determine the best combination of the various components used in the procedure, in order to benchmark the current existing knowledge on four different datasets from the literature. By varying the network topology, resource scarceness and the size of the projects, the computational experiments are carried out on a diverse set of projects. The procedure was able to find some new lower bounds and optimal solutions for the PSPLIB instances. Moreover, new best known results are reported for other, more diverse datasets that can be used in future research studies. The experiments revealed that even project instances with 30 activities cannot be solved to optimality when the topological structure is varied.

      PubDate: 2018-02-04T23:05:50Z
      DOI: 10.1016/j.cor.2018.01.017
      Issue No: Vol. 93 (2018)
       
  • Combining Benders decomposition and column generation for multi-activity
           tour scheduling
    • Authors: Maria I. Restrepo; Bernard Gendron; Louis-Martin Rousseau
      Pages: 151 - 165
      Abstract: Publication date: May 2018
      Source:Computers & Operations Research, Volume 93
      Author(s): Maria I. Restrepo, Bernard Gendron, Louis-Martin Rousseau
      This paper presents a method that combines Benders decomposition and column generation to solve the multi-activity tour scheduling problem. The Benders decomposition approach iterates between a master problem that links daily shifts with tour patterns and a set of daily subproblems that assign work activities and breaks to the shifts. Due to its structure, the master problem is solved by column generation. We exploit the expressiveness of context-free grammars to model and solve the Benders subproblems. Computational results show that our method outperforms a branch-and-price approach and is able to find high-quality solutions for weekly instances dealing with up to ten work activities. The adaptation of the method to the shift scheduling problem (the special case defined on a single day) is also shown to outperform the solution of a grammar-based model by a state-of-the-art mixed-integer programming solver on instances with up to 30 work activities.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.01.014
      Issue No: Vol. 93 (2018)
       
  • Recent research developments of strategic consumer behavior in operations
           management
    • Authors: Mike Mingcheng Wei; Fuqiang Zhang
      Pages: 166 - 176
      Abstract: Publication date: May 2018
      Source:Computers & Operations Research, Volume 93
      Author(s): Mike Mingcheng Wei, Fuqiang Zhang
      Strategic consumer behavior has been extensively studied in the Management Science and Operations Management community. We survey recent developments in the literature and review possible operational strategies and decisions to counteract the adverse impact of strategic consumer behavior. Specifically, we broadly characterize these decisions into three classes – Pricing, Inventory, and Information – and further discuss the influence of strategic consumer behavior on these decisions and their underlying mechanisms on counteracting consumers’ strategic waiting behavior.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2017.12.005
      Issue No: Vol. 93 (2018)
       
  • A shortest-path-based approach for the stochastic knapsack problem with
           non-decreasing expected overfilling costs
    • Authors: Troels Martin Range; Dawid Kozlowski; Niels Chr. Petersen
      Abstract: Publication date: Available online 21 April 2018
      Source:Computers & Operations Research
      Author(s): Troels Martin Range, Dawid Kozlowski, Niels Chr. Petersen
      The knapsack problem (KP) is concerned with the selection of a subset of multiple items with known positive values and weights such that the total value of selected items is maximized and their total weight does not exceed capacity. Item values, item weights, and capacity are known in the deterministic case. We consider the stochastic KP (SKP) with stochastic item weights. For this variant of the SKP we combine the chance constrained KP (CCKP) and the SKP with simple recourse (SRKP). The chance constraint allows for a violation of capacity, but the probability of a violation beyond an imposed limit is constrained. The violation of the capacity constraint is also included in the objective function in terms of a penalty function as in the SRKP. Penalty is an increasing function of the expected number of units of violation with proportionality as a special case. We formulate the SKP as a network problem and demonstrate that it can be solved by a label-setting dynamic programming approach for the shortest path problem with resource constraints (SPPRC). We develop a dominance criterion for an elimination of states in the dynamic programming approach using only the deterministic value of items along with mean and variance of the stochastic weight of items corresponding to the associated paths in the underlying network. It is shown that a lower bound for the impact of potential extensions of paths is available as an additional means to limit the number of states provided the penalty cost of expected overtime is convex. Our findings are documented in terms of a computational study.

      PubDate: 2018-04-24T22:15:13Z
      DOI: 10.1016/j.cor.2018.04.013
       
 
 
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