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

Author

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  • Abdulqader Othman Hamadameen
  • Nasruddin Hassan

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.

Suggested Citation

  • Abdulqader Othman Hamadameen & Nasruddin Hassan, 2018. "Pareto optimal solution for multiobjective stochastic linear programming problems with partial uncertainty," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 12(2), pages 139-166.
    • Handle: RePEc:ids:ijmore:v:12:y:2018:i:2:p:139-166
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