An Interactive Fuzzy Satisficing Method for Multiobjective Stochastic Integer Programming Problems through a Probability Maximization Model

نویسندگان

  • Cahit Perkgoz
  • Masatoshi Sakawa
  • Kosuke Kato
  • Hideki Katagiri
چکیده

In this paper, we deal with multiobjective integer programming problems involving random variable coefficients in objective functions and/or constraints. After reformulation of them on the basis of a probability maximization model for the chance constrained programming, incorporating fuzzy goals of the decision maker for the objective functions, we propose an interactive fuzzy satisficing method to derive a satisficing solution for the decision maker using genetic algorithms as a fusion of the stochastic programming and the fuzzy one.

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تاریخ انتشار 2005