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Genetic algorithm approach for solving multi-objective fuzzy stochastic programming problem

Author

Listed:
  • Sanjay Dutta
  • Srikumar Acharya
  • Rajashree Mishra

Abstract

This paper is concerned with the solution procedure of a multi-objective fuzzy stochastic optimisation problem by simulation-based genetic algorithm. In this article, a multi-objective fuzzy chance constrained programming problem is considered with continuous fuzzy random variables. The uncertain parameters are considered as fuzzy normal and fuzzy log-normal random variables. The feasibilities of the fuzzy chance constraints are checked by the fuzzy stochastic programming with the genetic process without deriving the deterministic equivalents. The proposed procedure is illustrated by a numerical example.

Suggested Citation

  • Sanjay Dutta & Srikumar Acharya & Rajashree Mishra, 2017. "Genetic algorithm approach for solving multi-objective fuzzy stochastic programming problem," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 11(1), pages 1-28.
    • Handle: RePEc:ids:ijmore:v:11:y:2017:i:1:p:1-28
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