Pareto optimal solution for multiobjective stochastic linear programming problems with partial uncertainty
by Abdulqader Othman Hamadameen; Nasruddin Hassan
International Journal of Mathematics in Operational Research (IJMOR), Vol. 12, No. 2, 2018

Abstract: A study on multiobjective stochastic linear programming (MSLP) problems with partial information on probability distribution is conducted. A method is proposed to utilise the concept of dominated solution for the multiobjective linear programming (MLP) problems, and find a pareto optimal solution (POS) without converting the MLP problem into its unique linear programming (LP) problem. An algorithm is proposed along with a numerical example which illustrated the practicability of the proposed algorithm. Comparison of results with existing methods shows the efficiency of the proposed method based on the analysis of results performed.

Online publication date: Tue, 06-Feb-2018

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