Integrated Optimization of Resilient Supply Chain Network Design and Operations Under Disruption Risks

Zhimin Guan, Jin Tao () and Minghe Sun
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Zhimin Guan: Northeastern University
Jin Tao: Henan University of Economics and Law
Minghe Sun: The University of Texas at San Antonio

A chapter in Supply Chain Risk Mitigation, 2022, pp 205-238 from Springer

Abstract: Abstract In recent years, supply chain disruptions caused by unexpected events have occurred more and more frequently, and these disruptions have been proven to have both short- and long-term negative impacts on supply chain operations and on corporate profitability. Thus, it is imperative to first analyze and understand the effects of these risks and then develop solutions to mitigate their impacts. In this study, an optimization approach is developed for integrated design and operations for resilient supply chain networks with disruption risk considerations. A mixed binary integer programming model is formulated for this purpose. Scenarios are used to describe disruption events of the facilities, and disruption events may take place at multiple facilities at the same time in a scenario. Uncertainties in supplies, demands, and prices are also considered. A region-wide dual-sourcing strategy, strategic emergency inventories, and alternative sourcing facilities are used in the supply chain network design stage to increase network resilience. The Sample Average Approximation method is used to solve the proposed model with disruption risk considerations. An illustrative example is used to demonstrate the validity of the model and sensitivity analysis results are reported to examine the effects of important parameters on the performance of the resulting resilient supply chain networks.

Date: 2022
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DOI: 10.1007/978-3-031-09183-4_10

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