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Two Bi-Objective Optimization Models For Competitive Location Problems

Author

Listed:
  • FENGMEI YANG

    (Faculty of Science, Beijing University of Chemical Technology, Beijing 100029, China)

  • GUOWEI HUA

    (Faculty of Science, Beijing University of Chemical Technology, Beijing 100029, China)

  • HIROSHI INOUE

    (School of Management, Tokyo University of Science, Kuki, Saitama 346-8512, Japan)

  • JIANMING SHI

    (Department of Computer Science and Systems Engineering, Muroran Institute of Technology, Hokkaido 050-8585, Japan)

Abstract

This paper deals with two bi-objective models arising from competitive location problems. The first model simultaneously intends to maximize market share and to minimize cost. The second one aims to maximize both profit and the profit margin. We study some of the related properties of the models, examine relations between the models and a single objective parametric integer programming problem, and then show how both bi-objective location problems can be solved through the use of a single objective parametric integer program. Based on this, we propose two methods of obtaining a set of efficient solutions to the problems of fundamental approach. Finally, a numerical example is presented to illustrate the solution techniques.

Suggested Citation

  • Fengmei Yang & Guowei Hua & Hiroshi Inoue & Jianming Shi, 2006. "Two Bi-Objective Optimization Models For Competitive Location Problems," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 5(03), pages 531-543.
    • Handle: RePEc:wsi:ijitdm:v:05:y:2006:i:03:n:s0219622006002118
    DOI: 10.1142/S0219622006002118
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    Cited by:

    1. Kun Guo & Qishan Zhang, 2017. "A Discrete Artificial Bee Colony Algorithm for the Reverse Logistics Location and Routing Problem," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(05), pages 1339-1357, September.
    2. Aslihan Yildiz & Ertugrul Ayyildiz & Alev Taskin Gumus & Coskun Ozkan, 2020. "A Modified Balanced Scorecard Based Hybrid Pythagorean Fuzzy AHP-Topsis Methodology for ATM Site Selection Problem," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(02), pages 365-384, March.

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