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Uncertain multi-objective programming model: a genetic algorithm approach

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  • Kailash Lachhwani

Abstract

This paper aims at describing an uncertain multi-objective programming model involving uncertain variables with genetic algorithm approach. In this paper, the uncertain multiobjective programming model is converted into an equivalent crisp mathematical programming model. Then, a genetic algorithm is proposed to search the Stackelberg-Nash equilibrium of the uncertain multiobjective programming model with supporting numerical illustrations. Finally, sensitivity analysis study is carried out over parameters of algorithm and solution obtained to show efficiency and robustness of genetic algorithm for uncertain multiobjective programming model.

Suggested Citation

  • Kailash Lachhwani, 2017. "Uncertain multi-objective programming model: a genetic algorithm approach," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 11(2), pages 271-283.
    • Handle: RePEc:ids:ijmore:v:11:y:2017:i:2:p:271-283
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