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Multi-Objective Programming for Supplier Selection and Order Allocation Under Disruption Risk and Demand, Quality, and Delay Time Uncertainties

Author

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  • Hanane Assellaou

    (LM2I Laboratory, ENSAM-Meknes, Mouly Ismail University, Meknes, Morocco)

  • Brahim Ouhbi

    (LM2I Laboratory, ENSAM-Meknes, Mouly Ismail University, Meknes, Morocco)

  • Bouchra Frikh

    (LTTI Laboratory, EST-Fès, Moulay Abdellah University, Fès, Morocco)

Abstract

The purpose of this article is to develop a new stochastic multi objective optimization model to mitigate disruption risks while simultaneously addressing operational risks as well. Indeed, this model considers five objective functions for selecting a set of suppliers considering disruption risk and stochastic demand, quality, and delay time. The authors use two types of risk evaluation models: value-at-risk (VaR) and conditional value-at-risk (CVaR). Two examples are given to illustrate our model and two solution methods are compared and tested.

Suggested Citation

  • Hanane Assellaou & Brahim Ouhbi & Bouchra Frikh, 2018. "Multi-Objective Programming for Supplier Selection and Order Allocation Under Disruption Risk and Demand, Quality, and Delay Time Uncertainties," International Journal of Business Analytics (IJBAN), IGI Global, vol. 5(2), pages 30-56, April.
    • Handle: RePEc:igg:jban00:v:5:y:2018:i:2:p:30-56
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    Cited by:

    1. Shilei Wang & Ying Ji & M. I. M. Wahab & Dan Xu & Changbao Zhou, 2022. "A New Decision Framework of Online Multi-Attribute Reverse Auctions for Green Supplier Selection under Mixed Uncertainty," Sustainability, MDPI, vol. 14(24), pages 1-23, December.

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