A proposed approach to solving multi-objective fuzzy stochastic linear programming problems with fuzzy probability

20.1001.1.27174409.1397.1.2.6.9/DOR

Abstract

In most of the phenomena we face, there is some kind of uncertainty. The basic problem in this field is first to identify the type of uncertainty and then to solve the models that face that type of uncertainty. Of course, some uncertainty environments do not have a good mathematical basis and use non-principled solving methods with great variety. One of the most important uncertainty environments that are widely used today is fuzzy and random environments, but in the face of today's phenomena, we find that the complexity of phenomena is such that it requires the simultaneous use of both random and fuzzy uncertainties. Hence the need to deal with fuzzy stochastic hybrid environments. Fuzzy stochastic programming is concerned with optimization problems in which some or all of its parameters are in the form of fuzzy stochastic variables. This paper presents an approach to solving multi-objective fuzzy stochastic linear programming problems. First, the multi-objective fuzzy stochastic model is transformed into a definite equivalent multi-objective linear programming model using the odds constraint probability programming approach with fuzzy probability and the alpha-cut concept, and then the resulting model is solved by adopting a fuzzy approach.

Keywords

References

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History

  • Receive Date: 05 March 2019
  • Accept Date: 16 April 2019

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