Journal of Operational Research and Its Applications ( Applied Mathematics ) - Lahijan Azad University

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Since most real-world decision problems, because of incomplete information or the existence of linguistic information in the data are including uncertainties. Stochastic programming and fuzzy programming as two conventional approaches to such issues have been raised. Stochastic programming deals with optimization problems where some or all the parameters are described by stochastic variables. In this paper, a method is provided for solving multi-objective stochastic programming Where the unknown parameters have been considered as random variables normal. In this model, it is assumed that the parameters specified by the relevant professionals. Since there aren't enough ways to solve such problems directly, the corresponding model using chance-constraint approach to convert to a certain multi-objective problem. Then, a fuzzy programming technique for solving the certain multi-objective model. In this paper, In this paper, the membership function is used hyperbolic. The final method can be solved by standard methods of nonlinear programming. Finally, numerical examples are provided to illustrate the operation of the proposed method.

Keywords: Stochastic programming, fuzzy programming, chance-constraint approach, hyperbolic membership function.

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