Resilient supply chain network design with proactive and reactive strategies under major disruptions

This paper discusses the influence of major disruptions, especially their ripple effects, on strategic and tactical decisions from the perspective of quantitative analysis. To mitigate the adverse consequence, we introduce proactive and reactive strategies and investigate the performance of these strategies. Considering the risk preference of decision-makers, we formulate the above problem as uncertain programming models under three different criteria (minimizing the expected cost, optimistic cost, and pessimistic cost). In the presented models, the side consequences and ripple effects of major disruptions are quantified by the facility capacity loss, production cost variation, and demand shift using uncertainty theory since disruption-related data are limited. Then, the developed models are converted into crisp deterministic ones with the aid of inverse distributions. Finally, we conduct a series of numerical experiments based on a real-world geographic data set of China to illustrate the validity of the presented models. The comparison between resilient solutions for the resilient supply portfolios and the non-resilient solutions with no measures available demonstrates the effectiveness of developed strategies in mitigating the ripple effects. Confronted with uncertainty of production cost, decision-makers are advised to adopt the reactive strategy, rather than the proactive strategy.