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Multiple sourcing under supplier failure risk and quantity discount: A genetic algorithm approach

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  • Meena, P.L.
  • Sarmah, S.P.

Abstract

This paper investigates an order allocation problem of a manufacturer/buyer among multiple suppliers under the risks of supply disruption. A mixed integer non-linear programming (MINLP) model is developed for order allocation considering different capacity, failure probability and quantity discounts for each supplier. We have shown that the formulated problem is NP-hard in nature and genetic algorithm (GA) approach is used to solve it. The model is illustrated through a numerical study and the result portrays that the cost of supplier has more influence on order quantity allocation rather than supplier’s failure probability.

Suggested Citation

  • Meena, P.L. & Sarmah, S.P., 2013. "Multiple sourcing under supplier failure risk and quantity discount: A genetic algorithm approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 50(C), pages 84-97.
    • Handle: RePEc:eee:transe:v:50:y:2013:i:c:p:84-97
    DOI: 10.1016/j.tre.2012.10.001
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    References listed on IDEAS

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    Cited by:

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    15. Torabi, S.A. & Baghersad, M. & Mansouri, S.A., 2015. "Resilient supplier selection and order allocation under operational and disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 22-48.
    16. Salehi Sadghiani, N. & Torabi, S.A. & Sahebjamnia, N., 2015. "Retail supply chain network design under operational and disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 75(C), pages 95-114.
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    19. Li, Xin & Ventura, José A. & Venegas, Bárbara B. & Kweon, Sang Jin & Hwang, Seong Wook, 2018. "An integrated acquisition policy for supplier selection and lot sizing considering total quantity discounts and a quality constraint," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 119(C), pages 19-40.
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