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Optimising two-stage robust supplier selection and order allocation problem under risk-averse criterion

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  • Yuqiang Feng
  • Yanju Chen
  • Yankui Liu

Abstract

This paper studies the supplier selection and order allocation (SS&OA) problem, where risks include a series of disruption scenarios with uncertain probability of occurrence. It is a challenge for industry decision-makers to balance the average cost and the level of risk under the ambiguity set for probabilities. To address this challenge, a two-stage distributionally robust (DR) Mean-CVaR model is presented for the SS&OA problem. A procedure is developed for constructing the ambiguity set, and Polyhedral and Box ambiguity sets are constructed to characterise the uncertain probabilities. The worst-case Mean-CVaR criterion is employed for the second-stage cost within the ambiguity set to trade off the expected cost and CVaR value. Three measures are incorporated to increase the resilience of the supply chain. The proposed robust model is reformulated into two mixed-integer linear programming models. A real case of the Huawei cell phone manufacturer is used to illustrate the validity of the proposed approach in numerical settings. Experimental results show that the new optimising approach can provide a robust SS&OA solution to immunise against the influence caused by uncertain probabilities. By comparative analyses, some management insights are obtained for industry decision-makers.

Suggested Citation

  • Yuqiang Feng & Yanju Chen & Yankui Liu, 2023. "Optimising two-stage robust supplier selection and order allocation problem under risk-averse criterion," International Journal of Production Research, Taylor & Francis Journals, vol. 61(19), pages 6356-6380, October.
  • Handle: RePEc:taf:tprsxx:v:61:y:2023:i:19:p:6356-6380
    DOI: 10.1080/00207543.2022.2127963
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    Cited by:

    1. Jin, Zhongyi & Ng, Kam K.H. & Zhang, Chenliang & Liu, Wei & Zhang, Fangni & Xu, Gangyan, 2024. "A risk-averse distributionally robust optimisation approach for drone-supported relief facility location problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).

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