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An Equilibrium Chance‐Constrained Multiobjective Programming Model with Birandom Parameters and Its Application to Inventory Problem

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  • Zhimiao Tao
  • Jiuping Xu

Abstract

An equilibrium chance‐constrained multiobjective programming model with birandom parameters is proposed. A type of linear model is converted into its crisp equivalent model. Then a birandom simulation technique is developed to tackle the general birandom objective functions and birandom constraints. By embedding the birandom simulation technique, a modified genetic algorithm is designed to solve the equilibrium chance‐constrained multiobjective programming model. We apply the proposed model and algorithm to a real‐world inventory problem and show the effectiveness of the model and the solution method.

Suggested Citation

  • Zhimiao Tao & Jiuping Xu, 2013. "An Equilibrium Chance‐Constrained Multiobjective Programming Model with Birandom Parameters and Its Application to Inventory Problem," Journal of Applied Mathematics, John Wiley & Sons, vol. 2013(1).
    • Handle: RePEc:wly:jnljam:v:2013:y:2013:i:1:n:382620
    DOI: 10.1155/2013/382620
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    References listed on IDEAS

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    1. Abebe Geletu & Michael Klöppel & Hui Zhang & Pu Li, 2013. "Advances and applications of chance-constrained approaches to systems optimisation under uncertainty," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(7), pages 1209-1232.
    2. Baker, H. & Ehrhardt, R., 1995. "A dynamic inventory model with random replenishment quantities," Omega, Elsevier, vol. 23(1), pages 109-116, February.
    3. Zhou, Gengui & Gen, Mitsuo, 1999. "Genetic algorithm approach on multi-criteria minimum spanning tree problem," European Journal of Operational Research, Elsevier, vol. 114(1), pages 141-152, April.
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