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  Subjects -> BUSINESS AND ECONOMICS (Total: 3096 journals)
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BUSINESS AND ECONOMICS (1141 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: 23)
Acta Amazonica     Open Access   (Followers: 3)
Acta Commercii     Open Access   (Followers: 2)
Acta Oeconomica     Full-text available via subscription   (Followers: 2)
Acta Scientiarum. Human and Social Sciences     Open Access   (Followers: 4)
Acta Universitatis Danubius. Œconomica     Open Access  
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: 12)
AfricaGrowth Agenda     Full-text available via subscription   (Followers: 1)
African Affairs     Hybrid Journal   (Followers: 56)
African Development Review     Hybrid Journal   (Followers: 33)
African Journal of Business and Economic Research     Full-text available via subscription   (Followers: 1)
African Journal of Business Ethics     Open Access   (Followers: 7)
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: 130)
American Journal of Business     Hybrid Journal   (Followers: 15)
American Journal of Business and Management     Open Access   (Followers: 51)
American Journal of Business Education     Open Access   (Followers: 10)
American Journal of Economics and Business Administration     Open Access   (Followers: 24)
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: 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: 26)
ANALES de la Universidad Central del Ecuador     Open Access   (Followers: 1)
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: 29)
Applied Developmental Science     Hybrid Journal   (Followers: 3)
Applied Economics     Hybrid Journal   (Followers: 44)
Applied Economics Letters     Hybrid Journal   (Followers: 29)
Applied Economics Quarterly     Full-text available via subscription   (Followers: 10)
Applied Financial Economics     Hybrid Journal   (Followers: 24)
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: 312)
Asia Pacific Viewpoint     Hybrid Journal  
Asia-Pacific Journal of Business Administration     Hybrid Journal   (Followers: 3)
Asia-Pacific Journal of Operational Research     Hybrid Journal   (Followers: 3)
Asian Business Review     Open Access   (Followers: 2)
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: 3)
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: 6)
Asian Journal of Sustainability and Social Responsibility     Open Access  
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: 22)
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)
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: 11)
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: 31)
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: 16)
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: 8)
Business Information Review     Hybrid Journal   (Followers: 13)
Business Management and Strategy     Open Access   (Followers: 40)
Business Research     Hybrid Journal   (Followers: 2)
Business Strategy and the Environment     Hybrid Journal   (Followers: 12)
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   (Followers: 1)
Cadernos EBAPE.BR     Open Access   (Followers: 1)
Cambridge Journal of Economics     Hybrid Journal   (Followers: 55)
Cambridge Journal of Regions, Economy and Society     Hybrid Journal   (Followers: 9)
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: 27)
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: 11)
Case Studies in Business and Management     Open Access   (Followers: 8)
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: 1)
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: 9)
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: 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: 2)
COEPTUM     Open Access  
Community Development Journal     Hybrid Journal   (Followers: 24)
Compensation & Benefits Review     Hybrid Journal   (Followers: 6)
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: 5)
Computational Economics     Hybrid Journal   (Followers: 9)
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 8)
Computer Law & Security Review     Hybrid Journal   (Followers: 15)
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: 6)
Corporate Communications An International Journal     Hybrid Journal   (Followers: 5)
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: 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: 4)
Cuadernos de Administración (Universidad del Valle)     Open Access   (Followers: 1)
Cuadernos de Economía     Open Access   (Followers: 1)
Cuadernos de Economia - Latin American Journal of Economics     Open Access   (Followers: 1)
Cuadernos de Estudios Empresariales     Open Access   (Followers: 1)
Current Opinion in Creativity, Innovation and Entrepreneurship     Open Access   (Followers: 8)
De Economist     Hybrid Journal   (Followers: 12)
Decision Analysis     Full-text available via subscription   (Followers: 8)
Decision Sciences     Hybrid Journal   (Followers: 15)
Decision Support Systems     Hybrid Journal   (Followers: 15)
Defence and Peace Economics     Hybrid Journal   (Followers: 16)
der markt     Hybrid Journal   (Followers: 1)
Desenvolvimento em Questão     Open Access  
Development     Full-text available via subscription   (Followers: 23)
Development and Change     Hybrid Journal   (Followers: 45)

        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  [3034 journals]
  • A multi-phase heuristic for the production routing problem
    • Abstract: Publication date: November 2017
      Source:Computers & Operations Research, Volume 87
      Author(s): Oğuz Solyalı, Haldun Süral
      This study considers the production routing problem where a plant produces and distributes a single item to multiple retailers over a multi-period time horizon. The problem is to decide on when and how much to produce and stock at the plant, when and how much to serve and stock at each retailer, and vehicle routes for shipments such that the sum of fixed production setup cost, variable production cost, distribution cost, and inventory carrying cost at the plant and retailers is minimized. A multi-phase heuristic is proposed for the problem. The proposed heuristic is a mathematical programming-based heuristic that relies on formulating and solving restricted versions of the problem as mixed integer programs. The computational experiments on benchmark instances show favorable results with regard to the quality of the solutions found at the expense of higher computing times on large instances. In particular, the heuristic managed to find new best solutions for the 65% of benchmark instances.

      PubDate: 2017-06-20T21:50:53Z
  • Lagrangian relaxation for SVM feature selection
    • Abstract: Publication date: November 2017
      Source:Computers & Operations Research, Volume 87
      Author(s): M. Gaudioso, E. Gorgone, M. Labbé, A.M. Rodríguez-Chía
      We discuss a Lagrangian-relaxation-based heuristics for dealing with feature selection in the Support Vector Machine (SVM) framework for binary classification. In particular we embed into our objective function a weighted combination of the L 1 and L 0 norm of the normal to the separating hyperplane. We come out with a Mixed Binary Linear Programming problem which is suitable for a Lagrangian relaxation approach. Based on a property of the optimal multiplier setting, we apply a consolidated nonsmooth optimization ascent algorithm to solve the resulting Lagrangian dual. In the proposed approach we get, at every ascent step, both a lower bound on the optimal solution as well as a feasible solution at low computational cost. We present the results of our numerical experiments on some benchmark datasets.

      PubDate: 2017-06-20T21:50:53Z
  • Expressiveness and robustness measures for the evaluation of an additive
           value function in multiple criteria preference disaggregation methods: An
           experimental analysis
    • Abstract: Publication date: November 2017
      Source:Computers & Operations Research, Volume 87
      Author(s): Miłosz Kadziński, Mohammad Ghaderi, Jakub Wąsikowski, Núria Agell
      An additive value function is one of the prevailing preference models in Multiple Criteria Decision Aiding (MCDA). Its indirect elicitation through pairwise questions is often applied due to lowering the cognitive effort on the part of a Decision Maker (DM). A practical usefulness of this approach is influenced by both expressiveness of the assumed model and robustness of the recommendation computed with its use. We experimentally evaluate the above characteristics in view of using an additive value function in the preference disaggregation context. The simulation results are quantified with the following four measures: (1) the share of decision scenarios for which a set of compatible value functions is non-empty, (2) the minimal difference between comprehensive values of reference alternatives compared pairwise by the DM, (3) the number of pairs of alternatives for which the necessary preference relation confirmed by all compatible functions holds, and (4) the number of non-trivial certain inferences which cannot be derived directly from the preference information. We discuss how these measures are influenced by the settings with different numbers of alternatives, criteria, pairwise comparisons, and performance distributions. We also study how the results change when applying various procedures for selection of the characteristic points which define the shape of per-criterion marginal value functions. In this regard, we compare four existing discretization algorithms with a new supervised technique proposed in this paper. Overall, we indicate that expressiveness and robustness are contradictory objectives, and a compromise between them needs to be reached to increase the usefulness of an additive value model in the preference disaggregation methods.

      PubDate: 2017-06-20T21:50:53Z
  • A decomposition based hybrid heuristic algorithm for the joint passenger
           and freight train scheduling problem
    • Abstract: Publication date: November 2017
      Source:Computers & Operations Research, Volume 87
      Author(s): Liang Liu, Maged Dessouky
      We study the joint problem of scheduling passenger and freight trains for complex railway networks, where the objective is to minimize the tardiness of passenger trains at station stops and the delay of freight trains. We model the problem as a mixed integer program and propose a two-step decomposition heuristic to solve the problem. The heuristic first vertically decomposes the train schedules into a passenger train scheduling phase and then a freight train scheduling phase. In the freight train scheduling phase, we use a train-based decomposition to iteratively schedule each freight train. Experimental results show the efficiency and quality of the proposed heuristic algorithm on real world size problems.

      PubDate: 2017-06-20T21:50:53Z
  • A variable neighborhood search and simulated annealing hybrid for the
           profile minimization problem
    • Abstract: Publication date: November 2017
      Source:Computers & Operations Research, Volume 87
      Author(s): Gintaras Palubeckis
      Given an undirected simple graph G, the profile minimization problem (PMP) is to find an ordering of the vertices of the graph G such that the sum of the profiles of all its vertices is minimized. The profile of the vertex v in position i is defined as max { 0 , i − h v } , where hv is the position of the leftmost vertex among all vertices adjacent to v in G. We propose an approach for the PMP, which combines a variable neighborhood search (VNS) scheme with the multi-start simulated annealing (MSA) technique. The solution delivered by MSA is submitted as input to the VNS component of the method. The VNS algorithm heavily relies on a fast insertion neighborhood exploration procedure. We show that the time complexity of this procedure is O(n 2), where n is the order of G. We have found empirically that it is advantageous to give between 50 and 75% of the computation time to MSA and the rest to VNS. The results of the computational experiments demonstrate the superiority of our MSA-VNS algorithm over the current state-of-the-art metaheuristic approaches for the PMP. Using MSA-VNS, we improved the best known solutions for 50 well-recognized benchmark PMP instances in the literature. The source code implementing MSA-VNS is made publicly available as a benchmark for future comparisons.

      PubDate: 2017-06-11T13:05:47Z
  • M/G/c/c state dependent queuing model for a road traffic system of two
           sections in tandem
    • Abstract: Publication date: November 2017
      Source:Computers & Operations Research, Volume 87
      Author(s): Nacira Guerouahane, Djamil Aissani, Nadir Farhi, Louiza Bouallouche-Medjkoune
      We propose in this article a M/G/c/c state dependent queuing model for road traffic flow. The model is based on finite capacity queuing theory which captures the stationary density-flow relationships. It is also inspired from the deterministic Godunov scheme for the road traffic simulation. We first present a reformulation of the existing linear case of M/G/c/c state dependent model, in order to use flow rather than speed variables. We then extend this model in order to consider upstream traffic demand and downstream traffic supply. After that, we propose the model for two road sections in tandem where both sections influence each other. In order to deal with this mutual dependence, we solve an implicit system given by an algebraic equation. Finally, we derive some performance measures (throughput and expected travel time). A comparison with results predicted by the M/G/c/c state dependent queuing networks shows that the model we propose here captures really the dynamics of the road traffic.

      PubDate: 2017-06-11T13:05:47Z
  • Airline flight schedule planning under competition
    • Abstract: Publication date: November 2017
      Source:Computers & Operations Research, Volume 87
      Author(s): Ahmed Abdelghany, Khaled Abdelghany, Farshid Azadian
      This paper presents a modeling framework for airline flight schedule planning under competition. The framework generates an operational flight timetable that maximizes the airline's revenue, while ensuring efficient utilization of the airline's resources (e.g. aircraft and crew). It explicitly considers passenger demand shift due to the network-level competition with other airlines. It also considers minimizing the needless ground time of the resources. The problem is formulated in the form of a bi-level mathematical program where the upper level represents the airline scheduling decisions, while the lower level captures passenger responses in terms of itinerary choices. A solution methodology is developed which integrates a meta- heuristic search algorithm, a network competition analysis model, and a resource (e.g. aircraft and crew) tracking model. The performance of the framework is evaluated through several experiments to develop the schedule for a major U.S. airline. The results demonstrate the success of the framework to develop a competitive schedule with efficient resources.

      PubDate: 2017-06-01T15:54:32Z
  • A stochastic model for the throughput analysis of passing dual yard cranes
    • Abstract: Publication date: November 2017
      Source:Computers & Operations Research, Volume 87
      Author(s): Suruchika Saini, Debjit Roy, René de Koster
      New container terminal technologies such as passing dual yard cranes per stack promise increase in stacking throughput capacity. However, dual yard cranes can interfere, which reduces the cranes’ throughput capacity. Using crane operational protocols, we develop a stochastic model for two passing dual yard cranes and obtain closed-form expressions for the crane throughput capacity with interference delays. We then develop an approximate model to estimate the expected throughput times for both balanced and unbalanced stack configuration. A detailed discrete-event simulation is built to validate the analytical model. We show that interference effects between the cranes can reduce the crane throughput capacity by an average of 35% and interference delays increase with an increase in the number of bays in the stack. We use the model to develop operational insights.

      PubDate: 2017-06-01T15:54:32Z
  • Large-scale vehicle routing problems: Quantum Annealing, tunings and
    • Abstract: Publication date: November 2017
      Source:Computers & Operations Research, Volume 87
      Author(s): A. Syrichas, A. Crispin
      Quantum Annealing was previously applied to the vehicle routing problem and the results were promising. For all benchmark instances in the study, optimal results were obtained. However, 100% success rate was not achieved in every case, and tuning the control parameters for larger instances proved cumbersome. This work addresses these remaining difficulties. An empirical approach is taken wherein measurements of run-time behaviour are exploited to transform existing good values of control parameters so that they can be used successfully for other problem instances. The course of this work shows a method which simplifies hand-tuning so that the heuristic performs successfully when applied to larger instances, and also demonstrates a tuning method which establishes control parameter values for instances which belong in broadly defined groupings. In addition, new best known solutions for large-scale instances, and initial results for the distance-constrained variant of the vehicle routing problem are presented.

      PubDate: 2017-06-01T15:54:32Z
  • A Relax-and-Cut framework for large-scale maximum weight connected
           subgraph problems
    • Abstract: Publication date: November 2017
      Source:Computers & Operations Research, Volume 87
      Author(s): Eduardo Álvarez-Miranda, Markus Sinnl
      Finding maximum weight connected subgraphs within networks is a fundamental combinatorial optimization problem both from theoretical and practical standpoints. One of the most prominent applications of this problem appears in Systems Biology and it corresponds to the detection of active subnetworks within gene interaction networks. Due to its importance, several modeling and algorithmic strategies have been proposed for tackling the maximum weight connected subgraph problem (MWCS) over the last years; the most effective strategies typically depend on the use of integer linear programming (ILP). Nonetheless, this implies that large-scale networks (such as those appearing in Systems Biology) can become burdensome; moreover, not all practitioners may have access to an ILP solver. In this paper, a unified modeling and algorithmic scheme is designed to solve the MWCS and some of its application-oriented variants with cardinality-constraints or budget-constraints. The proposed framework is based on a general node-based model which is tackled by a Relax-and-Cut scheme, i.e., Lagrangian relaxation combined with constraint generation; this yields a heuristic procedure capable of providing both dual and primal bounds. The approach is enhanced by additional valid inequalities, lifted valid inequalities, primal heuristics and variable-fixing procedures. Computational results on instances from the literature, as well as on additional large-scale instances, show that the proposed framework is competitive with respect to the existing approaches and it allows to find improved solutions for some unsolved instances from literature. The effect of initializing a Branch-and-Cut approach with information from the Relax-and-Cut is also investigated. The implemented approach is made available online.

      PubDate: 2017-06-01T15:54:32Z
  • GLNS: An effective large neighborhood search heuristic for the Generalized
           Traveling Salesman Problem
    • Abstract: Publication date: November 2017
      Source:Computers & Operations Research, Volume 87
      Author(s): Stephen L. Smith, Frank Imeson
      This paper presents a new solver for the exactly one-in-a-set Generalized Traveling Salesman Problem (GTSP). In the GTSP, we are given as input a complete directed graph with edge weights, along with a partition of the vertices into disjoint sets. The objective is to find a cycle (or tour) in the graph that visits each set exactly once and has minimum length. In this paper we present an effective algorithm for the GTSP based on adaptive large neighborhood search. The algorithm operates by repeatedly removing from, and inserting vertices in, the tour. We propose a general insertion mechanism that contains as special cases the well-known nearest, farthest and random insertion mechanisms. We provide extensive benchmarking results for our solver in comparison to the state-of-the-art on a wide range of existing and new problem libraries. We show that on the GTSP-LIB library, the proposed algorithm is competitive with the best known algorithms. On several other libraries, we show that given the same amount of time, the proposed solver finds higher quality solutions than existing approaches, particularly on harder instances that are non-metric and/or whose sets are not clustered.

      PubDate: 2017-05-27T07:30:00Z
  • Heuristics for the capacitated modular hub location problem
    • Abstract: Publication date: October 2017
      Source:Computers & Operations Research, Volume 86
      Author(s): Arild Hoff, Juanjo Peiró, Ángel Corberán, Rafael Martí
      In this paper we study the hub location problem, where the goal is to identify an optimal subset of facilities (hubs) to minimize the transportation cost while satisfying certain capacity constraints. In particular, we target the single assignment version, in which each node in the transportation network is assigned to only one hub to route its traffic. We consider here a realistic variant introduced previously, in which the capacity of edges between hubs is increased in a modular way. This reflects the practical situation in air traffic where the number of flights between two locations implies a capacity in terms of number of passengers. Then, the capacity can be increased in a modular way, as a factor of the number of flights. We propose heuristic methods to obtain high-quality solutions in short computing times. Specifically, we implement memory structures to create advanced search methods and compare them with previous heuristics on a set of benchmark instances. Memory structures have been widely implemented in the context of the tabu search methodology, usually embedded in local search algorithms. In this paper we explore an alternative design in which the constructive method is enhanced with frequency information and the local search is coupled with a path relinking post-processing. Statistical tests confirm the superiority of our proposal with respect to previous developments.

      PubDate: 2017-05-27T07:30:00Z
  • An iterative merging algorithm for soft rectangle packing and its
           extension for application of fixed-outline floorplanning of soft modules
    • Abstract: Publication date: October 2017
      Source:Computers & Operations Research, Volume 86
      Author(s): Pengli Ji, Kun He, Yan Jin, Hongsheng Lan, Chumin Li
      We address an important variant of the rectangle packing problem, the soft rectangle packing problem, and explore its problem extension for the fixed-outline floorplanning with soft modules. For the soft rectangle packing problem with zero deadspace, we present an iterative merging packing algorithm that merges all the rectangles into a final composite rectangle in a bottom-up order by iteratively merging two rectangles with the least areas into a composite rectangle, and then shapes and places each pair of sibling rectangles based on the dimensions and position of their composite rectangle in an up-bottom order. We prove that the proposed algorithm can guarantee feasible layout under some conditions, which are weaker as compared with a well-known zero-dead-space packing algorithm. We then provide a deadspace distribution strategy, which can systematically assign deadspace to modules, to extend the iterative merging packing algorithm to deal with soft packing problem with deadspace. For the fixed-outline floorplanning with soft modules problem, we propose an iterative merging packing based hierarchical partitioning algorithm, which adopts a general hierarchical partitioning framework as proposed in the popular PATOMA floorplanner. The framework uses a recursive bipartitioning method to partition the original problem into a set of subproblems, where each subproblem is a soft rectangle packing problem and how to solve the subproblem plays a key role in the final efficiency of the floorplanner. Different from the PATOMA that adopts the zero-dead-space packing algorithm, we adopt our proposed iterative merging packing algorithm for the subproblems. Experiments on the IBM-HB benchmarks show that the proposed packing algorithm is more effective than the zero-dead-space packing algorithm, and experiments on the GSRC benchmarks show that our floorplanning algorithm outperforms three state-of-the-art floorplanners PATOMA, DeFer and UFO, reducing wirelength by 0.2%, 4.0% and 2.3%, respectively.

      PubDate: 2017-05-27T07:30:00Z
  • A feasible flow-based iterative algorithm for the two-level hierarchical
           time minimization transportation problem
    • Abstract: Publication date: October 2017
      Source:Computers & Operations Research, Volume 86
      Author(s): Fanrong Xie, Muhammad Munir Butt, Zuoan Li
      The THTMTP (two-level hierarchical time minimization transportation problem) is an important problem arising in industries. In literature, there are only two approaches with shortcomings to solve the problem. In this paper, the THTMTP is formulated as a mathematical model applicable to the case in which the total available supply at the sources is no less than the total demand at the destinations. A feasible flow-based iterative algorithm named THTMTP-A is proposed to solve the THTMTP by constructing network with lower and upper arc capacities. It is proved that the THTMTP-A algorithm can find the optimal solution to the THTMTP in a polynomial time. The proposed THTMTP-A algorithm has good performance in terms of computer implementation, computational time and required memory for computation, and hence overcomes successfully the shortcomings of the two existing approaches. Computational experiments validate that the THTMTP-A algorithm is an efficient and robust method to solve the THTMTP, and can serve as efficient tool to solve other related optimization problems.

      PubDate: 2017-05-27T07:30:00Z
  • Comparison of formulations for the two-level uncapacitated facility
           location problem with single assignment constraints
    • Abstract: Publication date: October 2017
      Source:Computers & Operations Research, Volume 86
      Author(s): Bernard Gendron, Paul-Virak Khuong, Frédéric Semet
      We consider the two-level uncapacitated facility location problem with single assignment constraints (TUFLP-S), an extension of the uncapacitated facility location problem. We present six mixed-integer programming models for the TUFLP-S based on reformulation techniques and on the relaxation of the integrality of some of the variables associated with location decisions. We compare the models by carrying out extensive computational experiments on large, hard, artificial instances, as well as on instances derived from an industrial application in freight transportation.

      PubDate: 2017-05-22T07:20:07Z
  • Completion time variance minimisation on two identical parallel processors
    • Abstract: Publication date: October 2017
      Source:Computers & Operations Research, Volume 86
      Author(s): B. Srirangacharyulu
      The problem of scheduling jobs to minimise completion time variance (CTV) is a well-known problem in scheduling research. CTV is categorized as a non-regular performance measure and its value may decrease by increasing the job completion times. This objective is relevant in situations where providing uniform service to customers is important, and is in-line with just-in-time philosophy. The problem concerned in this paper is to schedule n jobs on two identical parallel machines to minimise CTV. We consider the unrestricted version of the problem. The problem is said to be restricted when a machine is not allowed to remain idle when jobs are available for processing. It may be necessary to delay the start of job processing on a machine in order to reduce the completion time deviations. This gives rise to the unrestricted version of the problem. We discuss several properties of an optimal schedule to the problem. In this paper, we develop a lower bound on CTV for a known partial schedule and propose a branch and bound algorithm to solve the problem. Optimal solutions are obtained and results are reported.

      PubDate: 2017-05-17T07:16:43Z
  • Frequency-driven tabu search for the maximum s-plex problem
    • Abstract: Publication date: October 2017
      Source:Computers & Operations Research, Volume 86
      Author(s): Yi Zhou, Jin-Kao Hao
      The maximum s-plex problem is an important model for social network analysis and other studies. In this study, we present an effective frequency-driven multi-neighborhood tabu search algorithm (FD-TS) to solve the problem on very large networks. The proposed FD-TS algorithm relies on two transformation operators (Add and Swap) to locate high-quality solutions, and a frequency-driven perturbation operator (Press) to escape and search beyond the identified local optimum traps. We report computational results for 47 massive real-life (sparse) graphs from the SNAP Collection and the 10th DIMACS Challenge, as well as 52 (dense) graphs from the 2nd DIMACS Challenge (results for 48 more graphs are also provided in the Appendix). We demonstrate the effectiveness of our approach by presenting comparisons with the current best-performing algorithms.

      PubDate: 2017-05-17T07:16:43Z
  • A decomposition approach for the p-median problem on disconnected graphs
    • Abstract: Publication date: October 2017
      Source:Computers & Operations Research, Volume 86
      Author(s): Agostinho Agra, Jorge Orestes Cerdeira, Cristina Requejo
      The p-median problem seeks for the location of p facilities on the vertices (customers) of a graph to minimize the sum of transportation costs for satisfying the demands of the customers from the facilities. In many real applications of the p-median problem the underlying graph is disconnected. That is the case of p-median problem defined over split administrative regions or regions geographically apart (e.g. archipelagos), and the case of problems coming from industry such as the optimal diversity management problem. In such cases the problem can be decomposed into smaller p-median problems which are solved in each component k for different feasible values of pk , and the global solution is obtained by finding the best combination of pk medians. This approach has the advantage that it permits to solve larger instances since only the sizes of the connected components are important and not the size of the whole graph. However, since the optimal number of facilities to select from each component is not known, it is necessary to solve p-median problems for every feasible number of facilities on each component. In this paper we give a decomposition algorithm that uses a procedure to reduce the number of subproblems to solve. Computational tests on real instances of the optimal diversity management problem and on simulated instances are reported showing that the reduction of subproblems is significant, and that optimal solutions were found within reasonable time.

      PubDate: 2017-05-17T07:16:43Z
  • An adaptive large neighborhood search metaheuristic for agile satellite
           scheduling with time-dependent transition time
    • Abstract: Publication date: October 2017
      Source:Computers & Operations Research, Volume 86
      Author(s): Xiaolu Liu, Gilbert Laporte, Yingwu Chen, Renjie He
      Agile satellites belong to the new generation of satellites with three degrees of freedom for acquiring images on the Earth. As a result, they have longer visible time windows for the requested targets. An image shot can be conducted at any time in the window if and only if the time left is sufficient for the fulfillment of the imaging process. For an agile satellite, a different observation time means a different image angle, thus defining a different transition time from its neighboring tasks. Therefore, the setup time for each imaging process depends on the selection of its observation start time, making the problem a time-dependent scheduling problem. To solve it, we develop a metaheuristic, called adaptive large neighborhood search (ALNS), thus creating a conflict-free observational timeline. ALNS is a local search framework in which a number of simple operators compete to modify the current solution. In our ALNS implementation, we define six removal operators and three insertion operators. At each iteration, a pair of operators is selected to destroy the current solution and generate a new solution with a large collection of variables modified. Time slacks are introduced to confine the propagation of the time-dependent constraint of transition time. Computational experiments show that the ALNS metaheuristic performs effectively, fulfilling more tasks with a good robustness.

      PubDate: 2017-05-12T08:55:49Z
  • A survey of maintenance and service logistics management: Classification
           and research agenda from a maritime sector perspective
    • Abstract: Publication date: September 2017
      Source:Computers & Operations Research, Volume 85
      Author(s): Ayse Sena Eruguz, Tarkan Tan, Geert-Jan van Houtum
      Maintenance and service logistics support are required to ensure high availability and reliability for capital goods and typically represent a significant part of operating costs in capital-intensive industries. In this paper, we present a classification of the maintenance and service logistics literature considering the key characteristics of a particular sector as a guideline, i.e., the maritime sector. We discuss the applicability and the shortcomings of existing works and highlight the lessons learned from a maritime sector perspective. Finally, we identify the potential future research directions and suggest a research agenda. Most of the maritime sector characteristics presented in this paper are also valid for other capital-intensive industries. Therefore, a big part of this survey is relevant and functional for industries such as aircraft/aerospace, defense, and automotive.

      PubDate: 2017-05-12T08:55:49Z
  • Corrigendum to “Hybrid metaheuristics for the clustered vehicle routing
           problem [Comput. Oper. Res., 58 (2015): 87–99]”
    • Abstract: Publication date: September 2017
      Source:Computers & Operations Research, Volume 85
      Author(s): Thibaut Vidal, Maria Battarra, Anand Subramanian, Güneş Erdoǧan

      PubDate: 2017-05-12T08:55:49Z
  • An improved Ant Colony System for the Sequential Ordering Problem
    • Abstract: Publication date: October 2017
      Source:Computers & Operations Research, Volume 86
      Author(s): Rafał Skinderowicz
      It is not rare that the performance of one metaheuristic algorithm can be improved by incorporating ideas taken from another. In this article we present how Simulated Annealing (SA) can be used to improve the efficiency of the Ant Colony System (ACS) and Enhanced ACS when solving the Sequential Ordering Problem (SOP). Moreover, we show how the very same ideas can be applied to improve the convergence of a dedicated local search, i.e. the SOP-3-exchange algorithm. A statistical analysis of the proposed algorithms both in terms of finding suitable parameter values and the quality of the generated solutions is presented based on a series of computational experiments conducted on SOP instances from the well-known TSPLIB and SOPLIB2006 repositories. The proposed ACS-SA and EACS-SA algorithms often generate solutions of better quality than the ACS and EACS, respectively. Moreover, the EACS-SA algorithm combined with the proposed SOP-3-exchange-SA local search was able to find 10 new best solutions for the SOP instances from the SOPLIB2006 repository, thus improving the state-of-the-art results as known from the literature. Overall, the best known or improved solutions were found in 41 out of 48 cases.

      PubDate: 2017-05-07T01:02:00Z
  • Exact computational solution of Modularity Density Maximization by
           effective column generation
    • Abstract: Publication date: October 2017
      Source:Computers & Operations Research, Volume 86
      Author(s): Rafael de Santiago, Luís C. Lamb
      Modularity Density Maximization (MDM) is associated with clustering problems in networks. MDM is an alternative to the resolution limit issue of the Modularity Maximization problem. Several reports in the literature have described mathematical programming models for MDM which solve instances of at most 40 nodes. In this context, this paper presents six new column generation methods that find exact solutions for the MDM problem. These methods use exact and auxiliary heuristic problems and an initial variable generator. Our methods show clear improvements over current results. Comparisons between our proposed methods and state-of-the-art algorithms are also carried out. Our results show that (i) two of our methods surpass the exact state-of-the-art algorithms in terms of time, and (ii) our methods provide optimal values for larger instances than current approaches can tackle.

      PubDate: 2017-05-07T01:02:00Z
  • Improving electromagnetism algorithm for solving resource allocation
           problem in stochastic networks
    • Abstract: Publication date: October 2017
      Source:Computers & Operations Research, Volume 86
      Author(s): Weng-Ming Chu, Koan-Yuh Chang
      This study investigates optimal resource allocation for minimizing total cost in stochastic networks (SN) where the duration of all activities involved is not only a random variable, but also a function of the resources allocated. The total cost of the network comprises resource usage cost and penalty cost. An Electromagnetism Algorithm (EA) is used as a decision tool for optimization and a Label-Correcting Tracing Algorithm (LCTA) for approximation of completion time in SN is suggested. Furthermore, the Critical Path Cluster Algorithm (CPCA) and Cluster Local Search Algorithm (CLSA) are developed to enhance EA's search ability for resource allocation. Results from numerical experiments show that the proposed EA yields good solution quality.

      PubDate: 2017-05-07T01:02:00Z
  • Energy-efficient bi-objective single-machine scheduling with power-down
    • Abstract: Publication date: September 2017
      Source:Computers & Operations Research, Volume 85
      Author(s): Ada Che, Xueqi Wu, Jing Peng, Pengyu Yan
      This paper considers a single-machine scheduling problem with power-down mechanism to minimize both total energy consumption and maximum tardiness. The aim is to find an optimal processing sequence of jobs and determine if the machine should be executed a power-down operation between two consecutive jobs. To formulate the problem, a mixed-integer linear programming (MILP) model is developed. Then a basic ε−constraint method is proposed to obtain the complete Pareto front of the problem. Considering the particularity of the problem, we also develop local search, preprocessing technique and valid inequalities to strengthen the basic ε−constraint method. Finally, to obtain approximate Pareto fronts for large-size problems, we utilize the method of cluster analysis to divide the jobs into several sorted clusters according to their release times and due dates. Any job in a preceding cluster must be processed before all jobs in a subsequent cluster. Thus, the solution space is reduced significantly. Computational experiments on benchmark and randomly generated instances demonstrate the effectiveness of the proposed exact and approximation approaches.

      PubDate: 2017-05-01T06:59:49Z
  • Improving the preconditioning of linear systems from interior point
    • Abstract: Publication date: September 2017
      Source:Computers & Operations Research, Volume 85
      Author(s): Luciana Casacio, Christiano Lyra, Aurelio Ribeiro Leite Oliveira, Cecilia Orellana Castro
      This paper deals with preconditioners for solving linear systems arising from interior point methods, using iterative methods. The main focus is the development of a set of results that allows a more efficient computation of the splitting preconditioner. During the interior point methods iterations, the linear system matrix becomes ill conditioned, leading to numerical difficulties to find a solution, even with iterative methods. Therefore, the choice of an effective preconditioner is essential for the success of the approach. The paper proposes a new ordering for a splitting preconditioner, taking advantage of the sparse structure of the original matrix. A formal demonstration shows that performing this new ordering the preconditioned matrix condition number is limited; numerical experiments reinforce the theoretical results. Case studies show that the proposed idea has better sparsity features than the original version of the splitting preconditioner and that it is competitive regarding the computational time.

      PubDate: 2017-04-24T06:57:10Z
  • A framework for secure IT operations in an uncertain and changing
    • Abstract: Publication date: September 2017
      Source:Computers & Operations Research, Volume 85
      Author(s): Andreas Schilling
      In this paper, a quantitative approach is proposed that addresses various decision making challenges within the IT security process of an organization. The approach serves as a framework that facilitates multiple applications to optimize the security of IT systems in different environmental settings. Addressing this problem is a critical challenge for almost all organizations and it still lacks a comprehensive and consistent quantitative treatment. The key question of the corresponding decision problem is which safeguards to select in order to achieve sufficient security. The proposed framework addresses this by establishing a generally applicable problem structure and by reusing existing knowledge in order to reduce implementation costs of the approach. Based on this foundation, efficient MILP models are applied to support the establishment of an effective IT security strategy. Depending on the knowledge an organization is able to provide, decisions take uncertainty and even dynamic aspects into account. As a result, deployed safeguards are robust against uncertain security threats and remain stable over several planning periods even if the system or the threat environment changes. This is a significant advancement that results in higher security in the short-term and lower costs in the mid- and long-term.

      PubDate: 2017-04-24T06:57:10Z
  • Scenario cluster Lagrangean decomposition for risk averse in multistage
           stochastic optimization
    • Abstract: Publication date: September 2017
      Source:Computers & Operations Research, Volume 85
      Author(s): Laureano F. Escudero, María Araceli Garín, Aitziber Unzueta
      In this work we present a decomposition approach as a mixture of dualization and Lagrangean Relaxation for obtaining strong lower bounds on large-sized multistage stochastic mixed 0–1 programs with a time stochastic dominance risk averse measure. The objective function to minimize is a composite function of the expected cost along the time horizon over the scenarios and the penalization of the expected cost excess on reaching the set of thresholds under consideration, subject to a bound on the expected cost excess for each threshold and a bound on the failure probability of reaching it. The main differences with some other risk averse strategies are presented. The problem is represented by a mixture of the splitting representation up to a given stage, so-called break stage, and the compact representation for the other stages along the time horizon. The dualization of the nonanticipativity constraints for the node-based and risk averse variables up to the break stage and the Lagrangean Relaxation of the cross node constraints of the risk averse strategy result in a model that can be decomposed into a set of independent scenario cluster submodels. Three Lagrangean multipliers updating schemes as the Subgradient method, the Lagrangean Progressive Hedging algorithm and the Dynamic Constrained Cutting Plane are computationally compared. We have observed in the randomly generated instances we have experimented with that the smaller the number of clusters, the stronger the lower bound provided for the original problem (even, frequently, it is the solution value) obtained with an affordable computing time.

      PubDate: 2017-04-24T06:57:10Z
  • Comprehensive review and evaluation of heuristics and meta-heuristics for
           two-sided assembly line balancing problem
    • Abstract: Publication date: August 2017
      Source:Computers & Operations Research, Volume 84
      Author(s): Zixiang Li, Ibrahim Kucukkoc, J. Mukund Nilakantan
      This paper presents a comprehensive review and evaluation of heuristics and meta-heuristics for the two-sided assembly line balancing problem. Though a few reviews have been presented, some latest methods are not included and there is no comparison of the meta-heuristics in terms of their performances. Furthermore, since various kinds of encoding schemes, decoding procedures and objective functions have been applied, the results cannot be generalized and the published comparison might be unfair. This paper contributes to knowledge by comparing the published methods, ranging from well-known simulated annealing to recent published iterated local search, and evaluating the six encoding schemes, 30 decoding procedures and five objective functions on the performances of the meta-heuristics meanwhile. The experimental design approach is applied to obtain valid and convincing results by testing algorithms under four termination criteria. Computational results demonstrate that the proper selection of encoding scheme, decoding procedure and objective function improves the performance of the algorithms by a significant margin. Another unique contribution of this paper is that 15 new best solutions are obtained for the large-sized type-II two-sided assembly line balancing problem during the re-implementation and evaluation of the meta-heuristics tested.

      PubDate: 2017-04-24T06:57:10Z
  • Solving large batches of traveling salesman problems with parallel and
           distributed computing
    • Abstract: Publication date: September 2017
      Source:Computers & Operations Research, Volume 85
      Author(s): S.G. Ozden, A.E. Smith, K.R. Gue
      In this paper, we describe and compare serial, parallel, and distributed solver implementations for large batches of Traveling Salesman Problems using the Lin–Kernighan Heuristic (LKH) and the Concorde exact TSP Solver. Parallel and distributed solver implementations are useful when many medium to large size TSP instances must be solved simultaneously. These implementations are found to be straightforward and highly efficient compared to serial implementations. Our results indicate that parallel computing using hyper-threading for solving 150- and 200-city TSPs can increase the overall utilization of computer resources up to 25% compared to single thread computing. The resulting speed-up/physical core ratios are as much as ten times better than a parallel and concurrent version of the LKH heuristic using SPC3 in the literature. For variable TSP sizes, a longest processing time first heuristic performs better than an equal distribution rule. We illustrate our approach with an application in the design of order picking warehouses.

      PubDate: 2017-04-17T06:54:27Z
  • Carousel greedy: A generalized greedy algorithm with applications in
    • Abstract: Publication date: September 2017
      Source:Computers & Operations Research, Volume 85
      Author(s): Carmine Cerrone, Raffaele Cerulli, Bruce Golden
      In this paper, we introduce carousel greedy, an enhanced greedy algorithm which seeks to overcome the traditional weaknesses of greedy approaches. We have applied carousel greedy to a variety of well-known problems in combinatorial optimization such as the minimum label spanning tree problem, the minimum vertex cover problem, the maximum independent set problem, and the minimum weight vertex cover problem. In all cases, the results are very promising. Since carousel greedy is very fast, it can be used to solve very large problems. In addition, it can be combined with other approaches to create a powerful, new metaheuristic. Our goal in this paper is to motivate and explain the new approach and present extensive computational results.

      PubDate: 2017-04-17T06:54:27Z
  • Clustered maximum weight clique problem: Algorithms and empirical analysis
    • Abstract: Publication date: September 2017
      Source:Computers & Operations Research, Volume 85
      Author(s): Krishna Teja Malladi, Snezana Mitrovic-Minic, Abraham P. Punnen
      We introduce the Clustered Maximum Weight Clique Problem (CCP), a generalization of the Maximum Weight Clique Problem, that models an image acquisition scheduling problem for a satellite constellation. The solution of CCP represents satellite schedules that satisfy customer requests for satellite imagery. Each request has a priority, an area of interest, and a time window. Often, the area of interest is too large to be imaged by one satellite pass and it has to be divided into several smaller images. Each image has one or more opportunities for an acquisition by a satellite. The problem is modeled by a clustered weighted graph. A graph node represents one opportunity for an image acquisition by one satellite. A graph edge indicates that either two opportunities are not in conflict – can both be in a schedule, or two opportunities are not acquiring the same image. Each graph node has a weight that represents the area size of the image. The graph nodes are partitioned into clusters each of which encompasses all the opportunities of one customer request. The priority of the request is captured by the cluster weight. The time window of the request restricts the number of opportunities. The CCP deals with finding a clique of a maximum weight where the weight combines the node weights and the cluster weights. More precisely, the cluster weight is multiplied by the contribution of the sum of the weights of the clique nodes. The contribution is either a linear function or a piece-wise linear function, where the latter is meant to favour finalizing an already partially served customer request. The paper presents several mathematical programming formulations of the CCP and proposes matheuristic solution approaches. The computational study is performed on the clustered adaptations of the DIMACS and BHOSLIB benchmark instances for the Maximum Weight Clique Problem. The achieved results are encouraging.

      PubDate: 2017-04-17T06:54:27Z
  • An exact algorithm for the modular hub location problem with single
    • Abstract: Publication date: September 2017
      Source:Computers & Operations Research, Volume 85
      Author(s): Moayad Tanash, Ivan Contreras, Navneet Vidyarthi
      A key feature of hub-and-spoke networks is the consolidation of flows at hub facilities. The bundling of flows allows reduction in the transportation costs, which is frequently modeled using a constant discount factor that is applied to the flow cost associated with all interhub links. In this paper, we study the modular hub location problem, which explicitly models the flow-dependent transportation costs using modular arc costs. It neither assumes a full interconnection between hub nodes nor a particular topological structure, instead it considers link activation decisions as part of the design. We propose a branch-and-bound algorithm that uses a Lagrangean relaxation to obtain lower and upper bounds at the nodes of the enumeration tree. Numerical results are reported for benchmark instances with up to 75 nodes.

      PubDate: 2017-04-10T08:46:08Z
  • Routing and scheduling decisions in the hierarchical hub location problem
    • Abstract: Publication date: September 2017
      Source:Computers & Operations Research, Volume 85
      Author(s): Okan Dukkanci, Bahar Y. Kara
      Hubs are facilities that consolidate and disseminate flow in many-to-many distribution systems. The hub location problem considers decisions that include the locations of hubs in a network and the allocations of demand (non-hub) nodes to these hubs. We propose a hierarchical multimodal hub network structure, and based on this network, we define a hub covering problem with a service time bound. The hierarchical network consists of three layers in which we consider a ring-star-star (RSS) network. This multimodal network may have different types of vehicles in each layer. For the proposed problem, we present and strengthen a mathematical model with some variable fixing rules and valid inequalities. Also, we develop a heuristic solution algorithm based on the subgradient approach to solve the problem in more reasonable times. We conduct the computational analysis over the Turkish network and the CAB data sets.

      PubDate: 2017-04-10T08:46:08Z
  • The Flexible Periodic Vehicle Routing Problem
    • Abstract: Publication date: September 2017
      Source:Computers & Operations Research, Volume 85
      Author(s): Claudia Archetti, Elena Fernández, Diana L. Huerta-Muñoz
      This paper introduces the Flexible Periodic Vehicle Routing Problem (FPVRP) where a carrier has to establish a distribution plan to serve his customers over a planning horizon. Each customer has a total demand that must be served within the horizon and a limit on the maximum quantity that can be delivered at each visit. A fleet of homogeneous capacitated vehicles is available to perform the services and the objective is to minimize the total routing cost. The FPVRP can be seen as a generalization of the Periodic Vehicle Routing Problem (PVRP) which instead has fixed service frequencies and schedules and where the quantity delivered at each visit is fixed. Moreover, the FPVRP shares some common characteristics with the Inventory Routing Problem (IRP) where inventory levels are considered at each time period and, typically, an inventory cost is involved in the objective function. We present a worst-case analysis which shows the advantages of the FPVRP with respect to both PVRP and IRP. Moreover, we propose a mathematical formulation for the problem, together with some valid inequalities. Computational results show that adding flexibility improves meaningfully the routing costs in comparison with both PVRP and IRP.
      Graphical abstract image

      PubDate: 2017-04-10T08:46:08Z
  • A parallel variable neighborhood search for the vehicle routing problem
           with divisible deliveries and pickups
    • Abstract: Publication date: September 2017
      Source:Computers & Operations Research, Volume 85
      Author(s): Olcay Polat
      A well-known variant of the vehicle routing problem involves backhauls, where vehicles deliver goods from a depot to linehaul customers and pick up goods from backhaul customers to the depot. The vehicle routing problem with divisible deliveries and pickups (VRPDDP) allows vehicles to visit each client once or twice for deliveries or pickups. In this study, a very efficient parallel approach based on variable neighborhood search (VNS) is proposed to solve VRPDDP. In this approach, asynchronous cooperation with a centralized information exchange strategy is used for parallelization of the VNS approach, called cooperative VNS (CVNS). All available problem sets of VRPDDP have been successfully solved with the CVNS, and the best solutions available in the literature have been significantly improved.

      PubDate: 2017-04-10T08:46:08Z
  • Minmax regret combinatorial optimization problems with investments
    • Abstract: Publication date: September 2017
      Source:Computers & Operations Research, Volume 85
      Author(s): Eduardo Conde, Marina Leal
      A new minmax regret optimization model in a system with uncertain parameters is proposed. In this model it is allowed to make investments before a minmax regret solution is implemented in order to modify the source or the nature of the existing uncertainty. Therefore, it is allowed to spend resources in order to change the basic cost structure of the system and take advantage of the modified system to find a robust solution. Some properties of this model allow us to have proper Mathematical Programming formulations that can be solved by standard optimization packages. As a practical application we consider the shortest path problem in a network in which it is possible to modify the uncertainty intervals for the arc costs by investing in the system. We also give an approximate algorithm and generalize some existing results on constant factor approximations.

      PubDate: 2017-04-02T19:46:05Z
  • High-performance technique for satellite range scheduling
    • Abstract: Publication date: September 2017
      Source:Computers & Operations Research, Volume 85
      Author(s): Kaiping Luo, Haihong Wang, Yijun Li, Qiang Li
      As the number of daily satellite service requests increases, the satellite range scheduling problem becomes more intractable during the ground station operations management. The NP-complete problem involves scheduling satellite requests to ground station antennas within their time windows so that the profit from the scheduled requests is maximized. This paper analyzes various conflicts between satellite requests and then develops a conflict-resolution technique. The technique first builds an elite initial schedule using a prescheduling strategy and then improves the initial schedule using a rescheduling strategy in a subspace of feasible solutions. The main highlight of the technique is its dual functions of quickly generating a high-quality solution and providing a good bound. As shown in the experimental results from the actual data and more difficult random instances, the proposed technique is significantly better than the best-known heuristic.

      PubDate: 2017-04-02T19:46:05Z
  • A Variable MIP Neighborhood Descent algorithm for managing inventory and
           distribution of cash in automated teller machines
    • Abstract: Publication date: September 2017
      Source:Computers & Operations Research, Volume 85
      Author(s): Homero Larrain, Leandro C. Coelho, Alejandro Cataldo
      In this paper we propose a new hybrid algorithm to solve mixed-integer programming (MIP) models called Variable MIP Neighborhood Search (VMND). The VMND relies on an existing mathematical formulation of the problem and significantly accelerates its resolution compared to standalone MIP solvers. Using this algorithm, we solve a practical problem arising in the ATM management and replenishment in Santiago, Chile. This rich and challenging problem, which we call the inventory-routing problem with cassettes and stockouts, shares much of its structure with the inventory-routing problem, but some features make it unique. We exploit the structure of the problem to derive neighborhoods implemented in our VMND, be it over routes, locations, periods or quantities delivered. Based on extensive computational experiments, our VMND is shown to significantly outperform benchmark solutions from a branch-and-cut algorithm. A sensitivity analysis is performed to confirm the robustness and effectiveness of our method.

      PubDate: 2017-04-02T19:46:05Z
  • Scheduling under the network of temporo-spatial proximity relationships
    • Abstract: Publication date: August 2017
      Source:Computers & Operations Research, Volume 84
      Author(s): Andrzej Kozik
      In this paper, we discuss and introduce to the scheduling field a novel optimization objective - half perimeter proximity measure in scheduling under the network of temporo-spatial proximity relationships. The presented approach enables to qualitatively express various reasons of scheduling certain jobs in close proximity, without resorting to quantitative, precisely defined consequences of such scheduling. Based on the correspondence between scheduling and rectangle packing problems in VLSI, we present an incremental Sequence Pair neighborhood evaluation algorithm, as an essential tool for complex solution-search methods for both proximity scheduling and physical layout synthesis of integrated circuits. A numerical experiment showed that such an incremental approach is considerably faster than the naive approach, performing evaluation of a solution from scratch each time, at the cost of small approximation error.

      PubDate: 2017-04-02T19:46:05Z
  • An open source Spreadsheet Solver for Vehicle Routing Problems
    • Abstract: Publication date: August 2017
      Source:Computers & Operations Research, Volume 84
      Author(s): Güneş Erdoğan
      The Vehicle Routing Problem (VRP) is one of the most frequently encountered optimization problems in logistics, which aims to minimize the cost of transportation operations by a fleet of vehicles operating out of a base. This paper introduces VRP Spreadsheet Solver, an open source Excel based tool for solving many variants of the Vehicle Routing Problem (VRP). Case studies of two real-world applications of the solver from the healthcare and tourism sectors that demonstrate its use are presented. The solution algorithm for the solver, and computational results on benchmark instances from the literature are provided. The solver is found to be capable of solving Capacitated VRP and Distance-Constrained VRP instances with up to 200 customers within 1 h of CPU time.

      PubDate: 2017-03-26T19:19:31Z
  • Integrating employee timetabling with scheduling of machines and
           transporters in a job-shop environment: A mathematical formulation and an
           Anarchic Society Optimization algorithm
    • Abstract: Publication date: August 2017
      Source:Computers & Operations Research, Volume 84
      Author(s): Amir Ahmadi-Javid, Pedram Hooshangi-Tabrizi
      This paper addresses a ternary-integration scheduling problem that incorporates employee timetabling into the scheduling of machines and transporters in a job-shop environment with a finite number of heterogeneous transporters where the objective is to minimize the completion time of all jobs. The problem is first formulated as a mixed-integer linear programming model. Then, an Anarchic Society Optimization (ASO) algorithm is developed to solve large-sized instances of the problem. The formulation is used to solve small-sized instances and to evaluate the quality of the solutions obtained for instances with larger sizes. A comprehensive numerical study is carried out to assess the performance of the proposed ASO algorithm. The algorithm is compared with three alternative metaheuristic algorithms. It is also compared with several algorithms developed in the literature for the integrated scheduling of machines and transporters. Moreover, the algorithms are tested on a set of adapted benchmark instances for an integrated problem of machine scheduling and employee timetabling. The numerical analysis suggests that the ASO algorithm is both effective and efficient in solving large-sized instances of the proposed integrated job-shop scheduling problem.

      PubDate: 2017-03-26T19:19:31Z
  • Towards hypercube queuing models for dispatch policies with priority in
           queue and partial backup
    • Abstract: Publication date: August 2017
      Source:Computers & Operations Research, Volume 84
      Author(s): Lásara Fabrícia Rodrigues, Reinaldo Morabito, Fernando Y. Chiyoshi, Ana Paula Iannoni, Cem Saydam
      This work extends the hypercube queuing model to explicitly address users’ in-queue priorities, as well as the partial backup of servers. To reduce the computational burden an approximate method is also developed. The study is motivated by an emergency maintenance service system found within the agricultural stage of the sugarcane agro-industry in Brazil. An example is used to illustrate the issues of priority in queue and partial backup. In order to show the importance and effectiveness of our proposed models we conducted additional experiments by varying the user arrival rates as well as eliminating the in-queue priorities. The study shows that selected adaptations and extensions of both the hypercube model and the approximate method are capable of representing similar emergency systems. The findings from the illustrative examples suggest promising perspectives for real-life applications in sugar and ethanol plants, and other agro-industries.

      PubDate: 2017-03-26T19:19:31Z
  • A strongly polynomial Contraction-Expansion algorithm for network flow
    • Abstract: Publication date: August 2017
      Source:Computers & Operations Research, Volume 84
      Author(s): Jean Bertrand Gauthier, Jacques Desrosiers, Marco E. Lübbecke
      This paper addresses the solution of the capacitated minimum cost flow problem on a network containing n nodes and m arcs. Satisfying necessary and sufficient optimality conditions can be done on the residual network although it can be quite time consuming as testified by the minimum mean cycle-canceling algorithm (MMCC). We introduce a contracted network which exploits these conditions on a much smaller network. Since the construction of this contracted network is very flexible, we study its properties depending on the construction choice. A generic contraction algorithm is then produced around the contracted network. Interestingly enough, it turns out it encapsulates both the MMCC and primal network simplex algorithms as extreme cases. By guiding the solution using a particular expansion scheme, we are able to recuperate theoretical results from MMCC. As such, we obtain a strongly polynomial Contraction-Expansion algorithm which runs in O(m 3 n 2) time. There is thus no improvement of the runtime complexity, yet the expansion scheme sticks to very practical observations of MMCC’s behavior, namely that of phases and jumps on the optimality parameter. The solution time is ultimately significantly reduced, even more so as the size of the instance increases.

      PubDate: 2017-03-20T12:25:55Z
  • Resource-constrained project scheduling with flexible resource profiles in
           continuous time
    • Abstract: Publication date: August 2017
      Source:Computers & Operations Research, Volume 84
      Author(s): Anulark Naber
      This paper addresses the resource-constrained project scheduling problem with flexible resource profiles (FRCPSP) in continuous time. In contrast to the discrete-time system, each task may start, end, or change its resource allocation at any point in time. The additional decisions for the continuous times of these events greatly amplify the problem complexity. We propose a mixed-integer linear programming model together with problem-specific inequalities and heuristic time limits, both of which are applied in the branch-and-cut procedure. In addition, the fractional period-width preprocessing and heuristic as well as the event estimation method are proposed to estimate the time and event parameters. Through the computational results, we investigate the pros and cons of the continuous-time model against the discrete-time counterpart both in terms of solution quality and runtimes, as well as the effectiveness of the preprocessing and different solution procedures.

      PubDate: 2017-03-20T12:25:55Z
  • Min-degree constrained minimum spanning tree problem with fixed centrals
           and terminals: Complexity, properties and formulations
    • Abstract: Publication date: August 2017
      Source:Computers & Operations Research, Volume 84
      Author(s): Fabio C.S. Dias, Manoel Campêlo, Críston Souza, Rafael Andrade
      We consider a variant of the Min-Degree Constrained Minimum Spanning Tree Problem where the central and terminal nodes are fixed a priori. We prove that the optimization problem is NP-Hard even for complete graphs and the feasibility problem is NP-Complete even if there is an edge between each central and each terminal in the input graph. Actually, this complexity result still holds when the minimum degree of each central node is restricted to be a same value d ≥ 2. We derive necessary and sufficient conditions for feasibility. We present several integer linear programming formulations – based on known formulations for the minimum spanning tree problem – along with a theoretical comparison among the lower bounds provided by their linear relaxations. We propose three Lagrangian heuristics. Computational experiments compare the performances of the heuristics and the formulations.

      PubDate: 2017-03-20T12:25:55Z
  • On minimization of the number of branches in branch-and-bound algorithms
           for the maximum clique problem
    • Abstract: Publication date: August 2017
      Source:Computers & Operations Research, Volume 84
      Author(s): Chu-Min Li, Hua Jiang, Felip Manyà
      When searching for a maximum clique in a graph G, branch-and-bound algorithms in the literature usually focus on the minimization of the number of branches generated at each search tree node. We call dynamic strategy this minimization without any constraint, because it induces a dynamic vertex ordering in G during the search. In this paper, we introduce a static strategy that minimizes the number of branches subject to the constraint that a static vertex ordering in G must be kept during the search. We analyze the two strategies and show that they are complementary. From this complementarity, we propose a new algorithm, called MoMC, that combines the strengths of the two strategies into a single algorithm. The reported experimental results show that MoMC is generally better than the algorithms implementing a single strategy.

      PubDate: 2017-03-08T13:52:25Z
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