A Parametric Technique Based on Simplex for Treating Stochastic Multicriteria Linear Programming Problem
[1]
Adel Mefleh Widyan, Department of Mathematics, Faculty of Science, Qassim University, Buraidah, Saudi Arabia.
Most of works treats the stochastic multicriteria optimization linear programming problem (SMOLPP) by transforming it to a deterministic one and solve it to obtain the efficient solutions. This paper introduced a new parametric technique based on the simplex algorithm for decomposing the parametric space of SMOLPP. The mathematical expectation approach will be used to transform the stochastic model with random variable in the objective functions to a deterministic one. Then, using the nonnegative weighted sum approach to scalarize the problem. A set of all efficient solutions can be determined using the proposed approach. A numerical example will be given to illustrate the proposed algorithm.
Stochastic Optimization, Multicriteria Programming, Parametric Study, Simplex Techniques
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