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A Discrete Particle Swarm Optimization Algorithm for Bi-Criteria Warehouse Location Problem

Author

Listed:
  • Fehmi Burcin Ozsoydan

    (Osmangazi University)

  • Tugba Sarac

    (Osmangazi University)

Abstract

The uncapacitated warehouse location problem (UWLP) is one of the widely studied discrete location problems, in which the nodes (customers) are connected to a number (w) of warehouses in such a way that the total cost, yields from the dissimilarities (distances) and from the fixed costs of the warehouses is minimized. Despite w is considered as fixed integer number, the UWLP is NP-hard. If the UWLP has two or more objective functions and w is an integer variable, the UWLP becomes more complex. Large size of this kind of complex problems can be solved by using heuristic algorithms or artificial intelligent techniques. It’s shown that Particle Swarm Optimization (PSO) which is one of the technique of artificial intelligent techniques, has achieved a notable success for continuous optimization, however, PSO implementations and applications for combinatorial optimization are still active research area that to the best of our knowledge fewer studies have been carried out on this topic. In this study, the bi-criteria UWLP of minimizing the total distance and total opening cost of warehouses. is presented and it’s shown that promising results are obtained.

Suggested Citation

  • Fehmi Burcin Ozsoydan & Tugba Sarac, 2011. "A Discrete Particle Swarm Optimization Algorithm for Bi-Criteria Warehouse Location Problem," Istanbul University Econometrics and Statistics e-Journal, Department of Econometrics, Faculty of Economics, Istanbul University, vol. 13(1), pages 114-124, Special I.
    • Handle: RePEc:ist:ancoec:v:13:y:2011:i:1:p:114-124
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    File URL: http://eidergisi.istanbul.edu.tr/sayi13/iueis13m7.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Warehouse Location Problem; Particle Swarm Optimization; Discrete Location Problems; Bi-criteria.;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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