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  Subjects -> BUSINESS AND ECONOMICS (Total: 3070 journals)
    - ACCOUNTING (88 journals)
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    - BUSINESS AND ECONOMICS (1145 journals)
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    - PUBLIC FINANCE, TAXATION (32 journals)
    - TRADE AND INDUSTRIAL DIRECTORIES (2 journals)

BUSINESS AND ECONOMICS (1145 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: 22)
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: 57)
African Development Review     Hybrid Journal   (Followers: 35)
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: 6)
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: 124)
American Economic Journal : Economic Policy     Full-text available via subscription   (Followers: 97)
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: 12)
American Journal of Finance and Accounting     Hybrid Journal   (Followers: 17)
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: 27)
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: 28)
Applied Economics Quarterly     Full-text available via subscription   (Followers: 10)
Applied Financial Economics     Hybrid Journal   (Followers: 23)
Applied Mathematical Finance     Hybrid Journal   (Followers: 6)
Applied Stochastic Models in Business and Industry     Hybrid Journal   (Followers: 6)
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: 322)
Asia Pacific Viewpoint     Hybrid Journal   (Followers: 1)
Asia-Pacific Journal of Business Administration     Hybrid Journal   (Followers: 3)
Asia-Pacific Journal of Operational Research     Hybrid Journal   (Followers: 3)
Asian Business Review     Open Access   (Followers: 2)
Asian Case Research Journal     Hybrid Journal   (Followers: 1)
Asian Development Review     Open Access   (Followers: 14)
Asian Economic Journal     Hybrid Journal   (Followers: 8)
Asian Economic Papers     Hybrid Journal   (Followers: 7)
Asian Economic Policy Review     Hybrid Journal   (Followers: 4)
Asian Journal of Accounting and Governance     Open Access   (Followers: 3)
Asian Journal of Business Ethics     Hybrid Journal   (Followers: 7)
Asian Journal of Social Sciences and Management Studies     Open Access   (Followers: 6)
Asian Journal of Technology Innovation     Hybrid Journal   (Followers: 8)
Asian-pacific Economic Literature     Hybrid Journal   (Followers: 6)
AStA Wirtschafts- und Sozialstatistisches Archiv     Hybrid Journal   (Followers: 5)
Atlantic Economic Journal     Hybrid Journal   (Followers: 14)
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: 21)
Australian Economic Review     Hybrid Journal   (Followers: 7)
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: 2)
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: 30)
Brookings Papers on Economic Activity     Open Access   (Followers: 47)
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: 16)
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: 11)
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: 25)
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 Journal of Operations Research     Hybrid Journal   (Followers: 5)
Central European Journal of Public Policy     Open Access   (Followers: 1)
CESifo Economic Studies     Hybrid Journal   (Followers: 15)
Chain Reaction     Full-text available via subscription  
Challenge     Full-text available via subscription   (Followers: 4)
China & World Economy     Hybrid Journal   (Followers: 15)
China : An International Journal     Full-text available via subscription   (Followers: 16)
China Economic Journal: The Official Journal of the China Center for Economic Research (CCER) at Peking University     Hybrid Journal   (Followers: 10)
China Economic Review     Hybrid Journal   (Followers: 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: 1)
COEPTUM     Open Access  
Community Development Journal     Hybrid Journal   (Followers: 23)
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: 47)
Development and Learning in Organizations     Hybrid Journal   (Followers: 7)

        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  [3030 journals]
  • Improving the preconditioning of linear systems from interior point
           methods
    • 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
           environment
    • 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
       
  • Editorial
    • Abstract: Publication date: August 2017
      Source:Computers & Operations Research, Volume 84
      Author(s): Boubaker DAACHI, Patrick SIARRY


      PubDate: 2017-04-24T06:57:10Z
       
  • Robust fuzzy 3D path following for autonomous underwater vehicle subject
           to uncertainties
    • Abstract: Publication date: August 2017
      Source:Computers & Operations Research, Volume 84
      Author(s): Xianbo Xiang, Caoyang Yu, Qin Zhang
      This paper addresses a three-dimensional (3D) path following control problem for underactuated autonomous underwater vehicle (AUV) subject to both internal and external uncertainties. A two-layered framework synthesizing the 3D guidance law and heuristic fuzzy control is proposed to achieve robust adaptive following along a predefined path. In the first layer, a 3D guidance controller for underactuated AUV is presented to guarantee the stability of path following in the kinematics stage. In the second layer, a heuristic adaptive fuzzy algorithm based on the guidance command and feedback linearization Proportional-Integral-Derivative (PID) controller is developed in the dynamics stage to account for the nonlinear dynamics and system uncertainties, including inaccuracy modelling parameters and time-varying environmental disturbances. Furthermore, the sensitivity analysis of the heuristic fuzzy controller is presented. Against most existing methods for 3D path following, the proposed robust fuzzy control scheme reduces the design and implementation costs of complicated dynamics controller, and relaxes the knowledge of the accuracy dynamics modelling and environmental disturbances. Finally, numerical simulation results validate the effectiveness of the proposed control framework and illustrate the outperformance of the proposed controller as well.

      PubDate: 2017-04-24T06:57:10Z
       
  • A meta-heuristic based goal-selection strategy for mobile robot search in
           an unknown environment
    • Abstract: Publication date: August 2017
      Source:Computers & Operations Research, Volume 84
      Author(s): Miroslav Kulich, Juan José Miranda-Bront, Libor Přeučil
      The single-robot search problem in an unknown environment is defined as the problem of finding a stationary object in the environment whose map is not known a priori. Compared to exploration, the only difference lies in goal selection as the objectives of search and exploration are dissimilar, i.e. a trajectory that is optimal in exploration does not necessarily minimize the expected value of the time to find an object along it. For this reason, in this paper we extend the preliminary ideas presented in Kulich et al. [1] to a general framework that accounts for the particular characteristics of the search problem. Within this framework, an important decision involved in the determination of the trajectory can be formulated as an instance of the Graph Search Problem (GSP), a generalization of the well-known Traveling Deliveryman Problem (TDP) which has not received much attention in the literature. We developed a tailored Greedy Randomized Adaptive Search Procedure (GRASP) meta-heuristic for the GSP, which generates good quality solutions in very short computing times and is incorporated in the overall framework. The proposed approach produces very good results in a simulation environment, showing that it is feasible from a computational standpoint and the proposed strategy outperforms the standard approaches.

      PubDate: 2017-04-24T06:57:10Z
       
  • A hybrid metaheuristic algorithm to optimise a real-world robotic cell
    • Abstract: Publication date: August 2017
      Source:Computers & Operations Research, Volume 84
      Author(s): Shi Qiang Liu, Erhan Kozan
      In this paper, a real-world robotic cell is investigated by transforming it into a special job shop with a set of stationary robots for manufacturing the parts of a product (i.e., operations of a job) at multiple operational stages. In addition, this robotic cell contains a particular mobile robot to transport the parts among stationary robots inside the cell as well as a depot (for initialising the production) and a stockpile (for stocking the complete products) outside the cell. Thus, a new scheduling problem called Blocking Job Shop Scheduling problem with Robotic Transportation (BJSSRT) is proposed. A numerical example is presented to illustrate the characteristics and complexity of BJSSRT. According to the problem properties, four types of robotic movements are defined for a mobile robot in an operation’s execution: processing-purpose, depot-purpose, return-purpose and stocking-purpose. By satisfying complex feasibility conditions, an innovative graph-based constructive algorithm is developed to produce a good feasible BJSSRT schedule. Embedded with the constructive algorithm, a hybrid Tabu Search and Threshold Accepting metaheuristic algorithm is developed to find a near-optimal solution in an efficient way. The proposed BJSSRT methodology has practical benefits in modelling the automated production system using stationary and mobile robots, especially in manufacturing and mining industries.

      PubDate: 2017-04-24T06:57:10Z
       
  • Bi-objective data gathering path planning for vehicles with bounded
           curvature
    • Abstract: Publication date: August 2017
      Source:Computers & Operations Research, Volume 84
      Author(s): Douglas G. Macharet, Jefferson W.G. Monteiro, Geraldo R. Mateus, Mario F.M. Campos
      A Wireless Sensor Network consists of several simple sensor nodes deployed in an environment having as primary goal data acquisition. However, due to limited sensor communication range, oftentimes it is necessary to use a mobile sink node that will visit sensor nodes to gather up their collected data. An important aspect that must be taken into account in this case are the intrinsic limitations of the vehicle used, such as kinematic and dynamic constraints, since most of the vehicles present in our everyday life have such restrictions. Therefore, this work addresses the problem of planning efficient paths, which are length and time of collection optimized for data gathering by a mobile robot with bounded curvature. We propose the use of the classical NSGA-II in order to tackle both objective functions. The methodology was evaluated through several experiments in a simulated environment. The results outperform the classical evolutionary approach to the single-objective problem specially considering the trade-off between overall length and collecting time.

      PubDate: 2017-04-24T06:57:10Z
       
  • Static force capability optimization of humanoids robots based on modified
           self-adaptive differential evolution
    • Abstract: Publication date: August 2017
      Source:Computers & Operations Research, Volume 84
      Author(s): Juliano Pierezan, Roberto Zanetti Freire, Lucas Weihmann, Gilberto Reynoso-Meza, Leandro dos Santos Coelho
      The current society requires solutions for many problems in safety, economy, and health. The social concerns on the high rate of repetitive strain injury, work-related osteomuscular disturbances, and domestic issues involving the elderly and handicapped are some examples. Therefore, studies on complex machines with structures similar to humans, known as humanoids robots, as well as emerging optimization metaheuristics have been increasing. The combination of these technologies may result in robust, safe, reliable, and flexible machines that can substitute humans in multiple tasks. In order to contribute to this topic, the static modeling of a humanoid robot and the optimization of its static force capability through a modified self-adaptive differential evolution (MSaDE) approach is proposed and evaluated in this study. Unlike the original SaDE, MSaDE employs a new combination of strategies and an adaptive scaling factor mechanism. In order to verify the effectiveness of the proposed MSaDE, a series of controlled experiments are performed. Moreover, some statistical tests are applied, an analysis of the results is carried out, and a comparative study of the MSaDE performance with other metaheuristics is presented. The results show that the proposed MSaDE is robust, and its performance is better than other powerful algorithms in the literature when applied to a humanoid robot model for the pushing and pulling tasks.

      PubDate: 2017-04-24T06:57:10Z
       
  • A variable neighborhood search algorithm for the surgery tactical planning
           problem
    • Abstract: Publication date: August 2017
      Source:Computers & Operations Research, Volume 84
      Author(s): Nico Dellaert, Jully Jeunet
      We address the tactical planning problem of surgeries that consists in building an admission plan of patients over a medium-term horizon planning so as to minimize over and under utilization of several resources such as operating theaters, beds and nursing care, compared with their target level of utilization. The problem is formulated as a mixed integer linear program for which exact solution methods fail to find an optimal solution in a reasonable execution time. We develop a Variable Neighborhood Search algorithm and show its ability to provide high quality solutions in short computational running times compared with CPLEX for numerous real-sized instances based on the surgery planning problem in a Dutch cardiothoracic center. Furthermore, with few parameters' settings and low computational memory requirements, this approach may easily be implemented in a decision support system for hospitals.

      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
           optimization
    • 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
           assignments
    • 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
       
  • A matheuristic based on large neighborhood search for the vehicle routing
           problem with cross-docking
    • Abstract: Publication date: August 2017
      Source:Computers & Operations Research, Volume 84
      Author(s): Philippe Grangier, Michel Gendreau, Fabien Lehuédé, Louis-Martin Rousseau
      The vehicle routing problem with cross-docking (VRPCD) consists in defining a set of routes that satisfy transportation requests between a set of pickup points and a set of delivery points. The vehicles bring goods from pickup locations to a cross-docking platform, where the items may be consolidated for efficient delivery. In this paper we propose a new solution methodology for this problem. It is based on large neighborhood search and periodically solving a set partitioning and matching problem with third-party solvers. Our method improves the best known solution in 19 of 35 instances from the literature.

      PubDate: 2017-04-02T19:46:05Z
       
  • Integrated aircraft-path assignment and robust schedule design with cruise
           speed control
    • Abstract: Publication date: August 2017
      Source:Computers & Operations Research, Volume 84
      Author(s): Özge Şafak, Si̇nan Gürel, M. Seli̇m Aktürk
      Assignment of aircraft types, each having different seat capacity, operational expenses and availabilities, critically affects airlines’ overall cost. In this paper, we assign fleet types to paths by considering not only flight timing and passenger demand, as commonly done in the literature, but also operational expenses, such as fuel burn and carbon emission costs associated with adjusting the cruise speed to ensure the passenger connections. In response to flight time uncertainty due to the airport congestions, we allow minor adjustments on the flight departure times in addition to cruise speed control, thereby satisfying the passenger connections at a desired service level. We model the uncertainty in flight duration via a random variable arising in chance constraints to ensure the passenger connections. Nonlinear fuel and carbon emission cost functions, chance constraints and binary aircraft assignment decisions make the problem significantly more difficult. To handle them, we use mixed-integer second order cone programming. We compare the performance of a schedule generated by the proposed model to the published schedule for a major U.S. airline. On the average, there exists a 20% overall operational cost saving compared to the published schedule. To solve the large scale problems in a reasonable time, we also develop a two-stage algorithm, which decomposes the problem into planning stages such as aircraft-path assignment and robust schedule generation, and then solves them sequentially.

      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
           problems
    • 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
       
  • A low-space algorithm for the subset-sum problem on GPU
    • Abstract: Publication date: July 2017
      Source:Computers & Operations Research, Volume 83
      Author(s): V.V. Curtis, C.A.A. Sanches
      We present a highly scalable parallel solution for the Subset-Sum Problem on Graphics Processing Units (GPUs) that substantially reduces the memory access by the device and, consequently, decreases the total runtime. We test this algorithm only on hard instances, which require the exhaustion of the entire search space, instead of simple random benchmarks. On a GPU with only 1.2 GB of global memory, we address hard instances with 100,000 items limited to 106 and 200 items limited to 108. Our algorithm achieves excellent runtimes outperforming the best-known practical and parallel algorithms, reaching speed-ups higher than 1000 in the best case compared to its sequential version.

      PubDate: 2017-03-20T12:25:55Z
       
  • Production planning in additive manufacturing and 3D printing
    • Abstract: Publication date: July 2017
      Source:Computers & Operations Research, Volume 83
      Author(s): Qiang Li, Ibrahim Kucukkoc, David Z. Zhang
      Additive manufacturing is a new and emerging technology and has been shown to be the future of manufacturing systems. Because of the high purchasing and processing costs of additive manufacturing machines, the planning and scheduling of parts to be processed on these machines play a vital role in reducing operational costs, providing service to customers with less price and increasing the profitability of companies which provide such services. However, this topic has not yet been studied in the literature, although cost functions have been developed to calculate the average production cost per volume of material for additive manufacturing machines. In an environment where there are machines with different specifications (i.e. production time and cost per volume of material, processing time per unit height, set-up time, maximum supported area and height, etc.) and parts in different heights, areas and volumes, allocation of parts to machines in different sets or groups to minimize the average production cost per volume of material constitutes an interesting and challenging research problem. This paper defines the problem for the first time in the literature and proposes a mathematical model to formulate it. The mathematical model is coded in CPLEX and two different heuristic procedures, namely ‘best-fit’ and ‘adapted best-fit’ rules, are developed in JavaScript. Solution-building mechanisms of the proposed heuristics are explained stepwise through examples. A numerical example is also given, for which an optimum solution and heuristic solutions are provided in detail, for illustration. Test problems are created and a comprehensive experimental study is conducted to test the performance of the heuristics. Experimental tests indicate that both heuristics provide promising results. The necessity of planning additive manufacturing machines in reducing processing costs is also verified.
      Graphical abstract image

      PubDate: 2017-03-15T14:03:24Z
       
  • 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
       
  • Multiobjective programming for sizing and locating biogas plants: A model
           and an application in a region of Portugal
    • Abstract: Publication date: July 2017
      Source:Computers & Operations Research, Volume 83
      Author(s): Sandra Silva, Luís Alçada-Almeida, Luís C. Dias
      The location of undesirable facilities involves economic, environmental and social impacts. The costs associated and the rejection of facilities by nearby population are crucial concerns. This paper introduces a Multiobjective Mixed-Integer Linear Programming (MMILP) approach to identify locations and capacities of biogas plants to treat animal waste from dairy farms, and assign each farm to a subset of the opened biogas plants. Three objectives were considered in the mathematical model: minimizing initial investment, operation and maintenance costs; minimizing transportation cost; and minimizing social rejection. The proposed model was applied to the Entre-Douro-e-Minho Region in Portugal. The approach provided as output a set of Pareto optimal solutions, represented by maps using a Geographic Information System, each one achieving a unique combination of economic and social performance.

      PubDate: 2017-03-08T13:52:25Z
       
  • Heuristic decision rules for short-term trading of renewable energy with
           co-located energy storage
    • Abstract: Publication date: July 2017
      Source:Computers & Operations Research, Volume 83
      Author(s): Michael Hassler
      In the last decade, the share of renewable energy sources in the energy mix has risen significantly in many countries, and the large-scale integration of these intermittent energy sources constitutes a major challenge to the power grid. A crucial building block of a successful transformation of today's energy systems is the use of energy storage, either co-located with renewable energy sources or on a grid-level. To this end, we present a model on the basis of a Markov Decision Process for the short-term trading of intermittent energy production co-located with energy storage. The model explicitly considers the time lag between trade and delivery of energy, which is characteristic for energy markets. Our storage representation includes asymmetrical conversion losses, asymmetrical power, and self-discharge. Stochastic production and market prices are represented by ARIMA processes, and the producer may also undertake price arbitrage by purchasing energy on the market when prices are comparatively low. Regarding the solution of our model, we develop several intuitive and easily interpretable decision rules that can be readily applied in practice. An extensive numerical study, based on real-world data, confirms the excellent performance of these rules in comparison to a sophisticated Approximate Dynamic Programming algorithm adapted from literature.

      PubDate: 2017-03-08T13:52:25Z
       
  • Quality assurance laboratory planning system to maximize worker preference
           subject to certification and preference balance constraints
    • Abstract: Publication date: July 2017
      Source:Computers & Operations Research, Volume 83
      Author(s): Alex J. Ruiz-Torres, Farzad Mahmoodi, Markku Kuula
      This research addresses the assignment of technicians to quality control tests in a pharmaceutical manufacturing environment. The problem is complex as it includes constraints related to the capabilities of the quality assurance technicians, as well as various criteria related to efficiency, customer service, and worker satisfaction. We consider several factors that are particular to labor scheduling in the pharmaceutical industry: preference to certain types of work and certification related to training in specific tests. We propose and utilize a technician satisfaction metric and develop a heuristic to maximize this measure. Experiments are performed in order to evaluate the performance of the proposed heuristic, and gain insights regarding the relationship among key experimental factors. The results demonstrate that, in general, the proposed heuristic quickly generates scheduling assignments that provide a very good approximation of the optimal solution.

      PubDate: 2017-03-02T07:28:25Z
       
  • Minmax scheduling with acceptable lead-times: Extensions to
           position-dependent processing times, due-window and job rejection
    • Abstract: Publication date: July 2017
      Source:Computers & Operations Research, Volume 83
      Author(s): Enrique Gerstl, Baruch Mor, Gur Mosheiov
      We focus on a due-date assignment model where due-dates are determined by penalties for jobs exceeding pre-specified (job-dependent, different) deadlines. The underlying assumption of this model, denoted by DIF, is that there are "lead times that customers consider to be reasonable and expected". In a minmax DIF model, the value of the objective function is that of the largest job/due-date cost. The goal is to find both the job sequence and the due-dates, such that this value is minimized. In this paper we study several extensions of the minmax DIF model. First, we consider general position-dependent job processing times. Then we extend the model to a setting of a due-window for acceptable lead-times. Here, the assumption is that a time interval exists, such that due-dates assigned to be within this interval are not penalized. The last extension of the DIF model is to a setting allowing job-rejection. This option reflects many real-life situations, where the scheduler may decide to process only a subset of the jobs, and the rejected jobs are penalized. The first two extensions are shown to be polynomially solvable: we introduce solution algorithms requiring O(n 3) and O(n 4) time, respectively, where n is the number of jobs. The last extension (assuming job-rejection) is proved to be NP-hard in the ordinary sense, and an efficient pseudo-polynomial dynamic programming algorithm is introduced.

      PubDate: 2017-03-02T07:28:25Z
       
  • A multi-tier linking approach to analyze performance of autonomous
           vehicle-based storage and retrieval systems
    • Abstract: Publication date: July 2017
      Source:Computers & Operations Research, Volume 83
      Author(s): Debjit Roy, Ananth Krishnamurthy, Sunderesh S. Heragu, Charles Malmborg
      To improve operational flexibility, throughput capacity, and responsiveness in order fulfillment operations, several distribution centers are implementing autonomous vehicle-based storage and retrieval system (AVS/RS) in their high-density storage areas. In such systems, vehicles are self-powered to travel in horizontal directions (x- and y- axes), and use lifts or conveyors for vertical motion (z-axis). In this research, we propose a multi-tier queuing modeling framework for the performance analysis of such vehicle-based warehouse systems. We develop an embedded Markov chain based analysis approach to estimate the first and second moment of inter-departure times from the load-dependent station within a semi-open queuing network. The linking solution approach uses traffic process approximations to analyze the performance of sub-models corresponding to individual tiers (semi-open queues) and the vertical transfer units (open queues). These sub-models are linked to form an integrated queuing network model, which is solved using an iterative algorithm. Performance estimates such as expected transaction cycle times and resource (vehicle and vertical transfer unit) utilization are determined using this algorithm, and can be used to evaluate a variety of design configurations during the conceptualization phase.

      PubDate: 2017-03-02T07:28:25Z
       
  • An exact hybrid method for the vehicle routing problem with time windows
           and multiple deliverymen
    • Abstract: Publication date: July 2017
      Source:Computers & Operations Research, Volume 83
      Author(s): Aldair Alvarez, Pedro Munari
      The vehicle routing problem with time windows and multiple deliverymen (VRPTWMD) is a variant of the vehicle routing problem with time windows in which service times at customers depend on the number of deliverymen assigned to the route that serves them. In particular, a larger number of deliverymen in a route leads to shorter service times. Hence, in addition to the usual routing and scheduling decisions, the crew size for each route is also an endogenous decision. This problem is commonly faced by companies that deliver goods to customers located in busy urban areas, a situation that requires nearby customers to be grouped in advance so that the deliverymen can serve all customers in a group during one vehicle stop. Consequently, service times can be relatively long compared to travel times, which complicates serving all scheduled customers during regular work hours. In this paper, we propose a hybrid method for the VRPTWMD, combining a branch-price-and-cut (BPC) algorithm with two metaheuristic approaches. We present a wide variety of computational results showing that the proposed hybrid approach outperforms the BPC algorithm used as standalone method in terms of both solution quality and running time, in some classes of problem instances from the literature. These results indicate the advantages of using specific algorithms to generate good feasible solutions within an exact method.

      PubDate: 2017-02-22T22:33:54Z
       
  • Lagrangian and branch-and-cut approaches for upgrading spanning tree
           problems
    • Abstract: Publication date: July 2017
      Source:Computers & Operations Research, Volume 83
      Author(s): Eduardo Álvarez-Miranda, Markus Sinnl
      Problems aiming at finding budget constrained optimal upgrading schemes to improve network performance have received attention over the last two decades. In their general setting, these problems consist of designing a network and, simultaneously, allocating (limited) upgrading resources in order to enhance the performance of the designed network. In this paper we address two particular optimal upgrading network design problems; in both cases, the sought-after layout corresponds to a spanning tree of the input network and upgrading decisions are to be taken on nodes. We design Mixed Integer Programming-based algorithmic schemes to solve the considered problems: Lagrangian relaxation approaches and branch-and-cut algorithms. Along with the designed algorithms, different enhancements, including valid inequalities, primal heuristic and variable fixing procedures, are proposed. Using two set of instances, we experimentally compare the designed algorithms and explore the benefits of the devised enhancements. The results show that the proposed approaches are effective for solving to optimality most of the instances in the testbed, or manage to obtain solutions and bounds giving very small optimality gaps. Besides, the proposed enhancements turn out to be beneficial for improving the performance of the algorithms.

      PubDate: 2017-02-22T22:33:54Z
       
  • A multi-start iterated local search algorithm for the generalized
           quadratic multiple knapsack problem
    • Abstract: Publication date: July 2017
      Source:Computers & Operations Research, Volume 83
      Author(s): Mustafa Avci, Seyda Topaloglu
      The quadratic multiple knapsack problem (QMKP) is a variant of the classical knapsack problem where multiple knapsacks are considered and the objective is to maximize a quadratic objective function subject to capacity constraints. The generalized quadratic multiple knapsack problem (G-QMKP) extends the QMKP by considering the setups, assignment conditions and the knapsack preferences of the items. In this study, a multi-start iterated local search algorithm (MS-ILS) in w the variable neighborhood descent (VND) algorithm is integrated with an adaptive perturbation mechanism is proposed to solve the G-QMKP. The multi-start implementation together with the adaptive perturbation mechanism enables the search process to explore different search regions in the search space while VND is applied to obtain high-quality solutions from the examined regions. Another remarkable feature of MS-ILS is its simplicity and adaptiveness that ease its implementation. The proposed MS-ILS is tested on G-QMKP benchmark instances derived from the literature. The results indicate that the developed MS-ILS can produce high-quality solutions for the G-QMKP. Particularly, it has been observed that the developed MS-ILS has improved the best known solutions for 35 out of 48 large-size G-QMKP instances.

      PubDate: 2017-02-22T22:33:54Z
       
  • Redistributing stock in library systems with a depot
    • Abstract: Publication date: July 2017
      Source:Computers & Operations Research, Volume 83
      Author(s): G. Van der Heide, K.J. Roodbergen, N.D. Van Foreest
      Public library organizations often utilize depots for carrying out shipments to libraries in case of stock-outs and for storing low demand rental items at low cost. Similar systems may be employed by rental companies for other rental products such as tools, DVDs, and jewelry. Since shipments deplete the depot’s inventory, stock must be taken back from the libraries in order to deal with future shipment requests. These shipment and take-back operations are carried out periodically, e.g. daily or weekly. This work focuses on optimizing the decisions for shipments and take-backs. We model the system by means of a Markov decision process and investigate its optimal policy for various problem instances. For the take-back decision, we distinguish between so-called threshold, reactive, and preventive take-backs. We use the insights from the MDP to develop a three-phase take-back heuristic. In experiments, our heuristic performs within 1% on average from the optimal solution. For settings with a large number of libraries, it is shown that an acceptable performance can be achieved by setting a base-stock level at the depot and taking back sufficient stock from the libraries to achieve this level.

      PubDate: 2017-02-22T22:33:54Z
       
  • A fast two-level variable neighborhood search for the clustered vehicle
           routing problem
    • Abstract: Publication date: July 2017
      Source:Computers & Operations Research, Volume 83
      Author(s): Christof Defryn, Kenneth Sörensen
      In this paper, we present an improved two-level heuristic to solve the clustered vehicle routing problem (CluVRP). The CluVRP is a generalization of the classical capacitated vehicle routing problem (CVRP) in which customers are grouped into predefined clusters, and all customers in a cluster must be served consecutively by the same vehicle. This paper contributes to the literature in the following ways: (i) new upper bounds are presented for multiple benchmark instances, (ii) good heuristic solutions are provided in much smaller computing times than existing approaches, (iii) the CluVRP is reduced to its cluster level without assuming Euclidean coordinates or distances, and (iv) a new variant of the CluVRP, the CluVRP with weak cluster constraints, is introduced. In this variant, clusters are allocated to vehicles in their entirety, but all corresponding customers can be visited by the vehicle in any order. The proposed heuristic solves the CluVRP by combining two variable neighborhood search algorithms, that explore the solution space at the cluster level and the individual customer level respectively. The algorithm is tested on different benchmark instances from the literature with up to 484 nodes, obtaining high quality solutions while requiring only a limited calculation time.

      PubDate: 2017-02-22T22:33:54Z
       
  • Real-time management of transportation disruptions in forestry
    • Abstract: Publication date: July 2017
      Source:Computers & Operations Research, Volume 83
      Author(s): Amine Amrouss, Nizar El Hachemi, Michel Gendreau, Bernard Gendron
      In this paper, we present a mathematical programming model based on a time-space network representation for solving real-time transportation problems in forestry. We cover a wide range of unforeseen events that may disrupt the planned transportation operations (e.g., delays, changes in the demand and changes in the topology of the transportation network). Although each of these events has different impacts on the initial transportation plan, one key characteristic of the proposed model is that it remains valid for dealing with all the unforeseen events, regardless of their nature. Indeed, the impacts of such events are reflected in a time-space network and in the input parameters rather than in the model itself. The empirical evaluation of the proposed approach is based on data provided by Canadian forestry companies and tested under generated disruption scenarios. The test sets have been successfully solved to optimality in short computational times and demonstrate the potential improvement of transportation operations incurred by this approach.

      PubDate: 2017-02-22T22:33:54Z
       
  • MIP neighborhood synthesis through semantic feature extraction and
           automatic algorithm configuration
    • Abstract: Publication date: July 2017
      Source:Computers & Operations Research, Volume 83
      Author(s): Tommaso Adamo, Gianpaolo Ghiani, Antonio Grieco, Emanuela Guerriero, Emanuele Manni
      The definition of a “good” neighborhood structure on the solution space is a key step when designing several types of heuristics for Mixed Integer Programming (MIP). Typically, in order to achieve efficiency in the search, the neighborhood structures need to be tailored not only to the specific problem but also to the peculiar distribution of the instances to be solved (reference instance population). Nowadays, this is done by human experts through a time-consuming process comprising: (a) problem analysis, (b) literature scouting and (c) experimentation. In this paper, we illustrate an Automatic Neighborhood Design algorithm that mimics steps (a) and (c). Firstly, the procedure extracts some semantic features from a MIP compact model. Secondly, these features are used to derive automatically some neighborhood design mechanisms. Finally, the “proper mix” of such mechanisms is sought through an automatic configuration phase performed on a training set representative of the reference instance population. When assessed on four well-known combinatorial optimization problems, our automatically-generated neighborhoods outperform state-of-the-art model-based neighborhoods with respect to both scalability and solution quality.

      PubDate: 2017-02-22T22:33:54Z
       
  • Column generation strategies and decomposition approaches for the
           two-stage stochastic multiple knapsack problem
    • Abstract: Publication date: July 2017
      Source:Computers & Operations Research, Volume 83
      Author(s): D.D. Tönissen, J.M. van den Akker, J.A. Hoogeveen
      Many problems can be formulated by variants of knapsack problems. However, such models are deterministic, while many real-life problems include some kind of uncertainty. Therefore, it is worthwhile to develop and test knapsack models that can deal with disturbances. In this paper, we consider a two-stage stochastic multiple knapsack problem. Here, we have a multiple knapsack problem together with a set of possible disturbances. For each disturbance, or scenario, we know its probability of occurrence and the resulting reduction in the sizes of the knapsacks. For each knapsack we decide in the first stage which items we take with us, and when a disturbance occurs we are allowed to remove items from the corresponding knapsack. Our goal is to find a solution where the expected revenue is maximized. We use branch-and-price to solve this problem. We present and compare two solution approaches: the separate recovery decomposition (SRD) and the combined recovery decomposition (CRD). We prove that the LP-relaxation of the CRD is stronger than the LP-relaxation of the SRD. Furthermore, we investigate numerous column generation strategies and methods to create additional columns outside the pricing problem. These strategies reduce the solution time significantly. To the best of our knowledge, there is no other paper that investigates such strategies so thoroughly.

      PubDate: 2017-02-22T22:33:54Z
       
  • Branch-and-price and adaptive large neighborhood search for the truck and
           trailer routing problem with time windows
    • Abstract: Publication date: July 2017
      Source:Computers & Operations Research, Volume 83
      Author(s): Sophie N. Parragh, Jean-François Cordeau
      Motivated by a situation faced by infrastructure service providers operating in urban areas with accessibility restrictions, we study the truck and trailer routing problem with time windows (TTRPTW). In this problem the vehicle fleet consists of trucks and trailers which may be decoupled. A set of customers has to be served and some of the customers can only be accessed by the truck without the trailer. This gives rise to the planning of truck-and-trailer routes containing truck-only subroutes, in addition to truck-only routes and truck-and-trailer routes without subroutes. We propose a branch-and-price algorithm for the TTRPTW, using problem specific enhancements in the pricing scheme and alternative lower bound computations. We also tailor an adaptive large neighborhood search algorithm to the TTRPTW in order to obtain good initial columns. When compared to existing metaheuristic algorithms we obtain highly competitive results. Some instances with up to 100 customers are solved to optimality with the proposed branch-and-price algorithm.

      PubDate: 2017-02-15T22:30:51Z
       
  • A new approach to cooperative competition in facility location problems:
           Mathematical formulations and an approximation algorithm
    • Abstract: Publication date: July 2017
      Source:Computers & Operations Research, Volume 83
      Author(s): Mohammad Rohaninejad, Hamidreza Navidi, Behdin Vahedi Nouri, Reza Kamranrad
      This paper deals with cooperative competition in facility location problems in which potential players (investors) are in competition (or conflict) over acquiring suitable sites and clients. In order to formulate the problem, a game-theoretical multi-objective model with the objective of maximizing investor utility is presented. In the proposed method, an acceptance threshold constraint is applied to facility allocation that is based on a combination of distance between a facility and clients, and investors’ product prices. Since the common solution methods for multi-objective optimization, such as weighted sums, ε-constraints, multi-objective meta-heuristic algorithms, etc. are not efficient enough, and cannot guarantee achieving Nash equilibrium points, a new approach is developed to solve the presented problem. Moreover, according to the computational complexity of the problem, an approximation algorithm is introduced for large-sized problems. Finally, the computational results demonstrate that the proposed algorithm performs efficiently in obtaining Nash equilibrium points.

      PubDate: 2017-02-15T22:30:51Z
       
 
 
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