Obtaining the Efficient Solutions for Multicriterion Programming Problems with Stochastic Parameters

Abstract

This paper deals with obtaining the set of efficient and non-dominatedfront solutions for the stochastic multicriterion programming problem(SMCPP) with random variables in both the objective functions and the right-hand side of the constraints. In this work, suggested approach uses the statistical inference in two stages, in one of them, The SMCPP is transformed into an equivalent deterministic multicriterion programming problem (DMCPP), then, in the other one, the nonnegative weighted sum approach will be applied to transform the multicriterion programming problem into a single objective programming problem.An illustrative example is presented to show the realistic implementation of the suggested approach