Minimax Relative Regret Approach for Resilient Supply Chain Design

Ming Liu (1) , Yueyu Ding (1) , Feng Chu (2) , Feifeng Zheng (3) , Chengbin Chu (4, 5)

1 Tongji University
2 IBISC - Informatique, BioInformatique, Systèmes Complexes
3 Donghua University [Shanghai]
4 ESIEE Paris
5 COSYS-GRETTIA - Génie des Réseaux de Transport Terrestres et Informatique Avancée

Uncertain disruption risks negatively influence the performance of supply chains by reducing the facilities' capacity. Proactive and recovery strategies for building resilient supply chains have received increasing attention from academia. Therefore, in this work, we study a resilient supply chain designing problem considering the uncertain occurrence and extent of disruptions, and the stochastic demand during time periods. For the problem, a two-stage min-max relative regret robust model is developed. The first stage is to determine the optimal facility locations and investments in protection systems, and the second stage decides the recovery actions and the quantity of products transported between different facilities and customers. The objective is to minimise the worst-case total relative regret cost. Finally, a case study is conducted, and some insights are given through the results of sensitivity analysis.

Keywords: Supply Chain Management; Supply chains and networks; Risk Management

Domains: Operations Research [math.OC]

Ming Liu, Yueyu Ding, Feng Chu, Feifeng Zheng, Chengbin Chu. Minimax Relative Regret Approach for Resilient Supply Chain Design. 10th IFAC Conference on Manufacturing Modelling, Management and Control (MIM 2022), Jun 2022, Nantes, France. pp.1465--1470, ⟨10.1016/j.ifacol.2022.09.597⟩. ⟨hal-03723134⟩