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An interactive fuzzy satisficing method for random fuzzy multiobjective integer programming problems through probability maximization with possibility

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Listed:
  • M. Sakawa

    (Hiroshima University)

  • T. Matsui

    (Hiroshima University)

  • H. Katagiri

    (Hiroshima University)

Abstract

This paper considers multiobjective integer programming problems where each coefficient of the objective functions is expressed by a random fuzzy variable. A new decision making model is proposed by incorporating the concept of probability maximization into a possibilistic programming model. For solving transformed deterministic problems, genetic algorithms with double strings for nonlinear integer programming problems are introduced. An interactive fuzzy satisficing method is presented for deriving a satisficing solution to a decision maker by updating the reference probability levels. An illustrative numerical example is provided to clarify the proposed method.

Suggested Citation

  • M. Sakawa & T. Matsui & H. Katagiri, 2013. "An interactive fuzzy satisficing method for random fuzzy multiobjective integer programming problems through probability maximization with possibility," Fuzzy Information and Engineering, Springer, vol. 5(3), pages 335-350, September.
  • Handle: RePEc:spr:fuzinf:v:5:y:2013:i:3:d:10.1007_s12543-013-0146-0
    DOI: 10.1007/s12543-013-0146-0
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    References listed on IDEAS

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    1. Peter Kall & János Mayer, 2011. "Stochastic Linear Programming," International Series in Operations Research and Management Science, Springer, edition 2, number 978-1-4419-7729-8, September.
    2. Fred Glover, 1989. "Tabu Search---Part I," INFORMS Journal on Computing, INFORMS, vol. 1(3), pages 190-206, August.
    3. Masatoshi Sakawa & Ichiro Nishizaki & Hideki Katagiri, 2011. "Fuzzy Multiobjective Stochastic Programming," International Series in Operations Research & Management Science, in: Fuzzy Stochastic Multiobjective Programming, chapter 0, pages 49-99, Springer.
    4. Masatoshi Sakawa & Kosuke Kato, 2008. "Interactive Fuzzy Multi-Objective Stochastic Linear Programming," Springer Optimization and Its Applications, in: Cengiz Kahraman (ed.), Fuzzy Multi-Criteria Decision Making, pages 375-408, Springer.
    5. George B. Dantzig, 1955. "Linear Programming under Uncertainty," Management Science, INFORMS, vol. 1(3-4), pages 197-206, 04-07.
    6. Sakawa, Masatoshi & Kato, Kosuke & Nishizaki, Ichiro, 2003. "An interactive fuzzy satisficing method for multiobjective stochastic linear programming problems through an expectation model," European Journal of Operational Research, Elsevier, vol. 145(3), pages 665-672, March.
    7. A. Charnes & W. W. Cooper, 1959. "Chance-Constrained Programming," Management Science, INFORMS, vol. 6(1), pages 73-79, October.
    8. Masatoshi Sakawa & Ichiro Nishizaki & Hideki Katagiri, 2011. "Fuzzy Stochastic Multiobjective Programming," International Series in Operations Research and Management Science, Springer, number 978-1-4419-8402-9, September.
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