Title: Pareto optimal solution for multiobjective stochastic linear programming problems with partial uncertainty

Authors: Abdulqader Othman Hamadameen; Nasruddin Hassan

Addresses: Department of Mathematical Sciences, Faculty of Science and Health, Koya Uiniversity, Koya KOY45, Kurdistan Region, Iraq ' School of Mathematical Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor DE, Malaysia

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.

Keywords: dominated solution; fuzzy transformation; MSLP problems; pareto optimal solution; POS; stochastic transformation.

DOI: 10.1504/IJMOR.2018.089675

International Journal of Mathematics in Operational Research, 2018 Vol.12 No.2, pp.139 - 166

Received: 19 Feb 2016
Accepted: 20 Jul 2016
Published online: 06 Feb 2018 *

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