Comparing Mitigation Strategies for Supply Chain under Operational Disruptions Using Monte Carlo Simulation

Abstract

Although supply chain disruptions have been under study since the 1990’s, they attracted more attention last year due to the COVID-19 pandemic. Not only researchers, but all people realized how disruptions can negatively affect the performance of business, and supply chains. Mitigation strategies are the way to “be better prepared” for such disruptions. This paper aims at evaluating the performance of five different mitigation strategies for a multi-period supply chain under operational disruptions. The disruptions under consideration are capacity, and demand disruptions, whether separate or simultaneous. Integer linear programming is used to design the supply chain network. Monte Carlo simulation is used to evaluate the performance of the proposed mitigation strategies under different disruption scenarios. Results reveal that the mitigation strategies that perform better regarding financial performance measures, perform worse regarding customer satisfaction performance measures. The model helps decision makers to decide the most suitable mitigation strategy according to their priorities.