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Article type: Research Article
Authors: Shi, Honghua | Ni, Yaodong; *
Affiliations: School of Information Technology and Management, University of International Business and Economics, Beijing, China
Correspondence: [*] Corresponding author. Yaodong Ni, School of Information Technology and Management, University of International Business and Economics, Beijing, China. E-mail: ni@uibe.edu.cn.
Abstract: Today’s supply chains have a greater likelihood of disruption risks than ever before. Sometimes, a lengthy recovery period is needed for supply chains to return to regular operation after being disrupted. During the recovery time window, how to increase the performance of supply chains is not sufficiently studied. Furthermore, the works considering parameter uncertainty arising from the lack of historical data are also limited. To address these problems, we formulate the recovery scheduling of supply chains under major disruption as mixed-integer linear programming models. In the presented models, outsourcing strategy and capacity expansion strategy are introduced to increase the service level of the supply chain after the disruption. The effects of disruption risks on supply chain performance are quantified using uncertainty theory in the absence of historical data. A set of computational examples illustrate that cost may increase markedly when more facilities are disrupted simultaneously. Thus, decision-makers have to pay close attention to supply chain disruption management and plan for disruption in advance. Moreover, the results suggest that outsourcing strategy is more useful to reduce cost when a higher service level is required.
Keywords: Supply chain, facility disruptions, recovery strategies, uncertainty
DOI: 10.3233/JIFS-202176
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 5, pp. 9669-9686, 2021
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