Responsive contingency planning in supply risk management by considering congestion effects

Contingency rerouting is known as a cost-effective risk management strategy for major disruptions such as earthquakes and natural disasters. The objective of this paper is to develop a decision-making tool to determine the appropriate response speed of a volume-flexible backup supplier to improve the supply chain responsiveness. We propose a mixed integer programming (MIP)-based capacity planning tool which generates the contingency plan of the supply chain subject to random disruptions. In order to make an accurate decision, the impact of critical operational characteristics such as response time and congestion are considered in a disruption scenario. The appropriate response speed is selected through a decision tree analysis by minimizing the expected supply chain costs. The selection is made with respect to three different attitudes of the decision maker towards risk. In order to evaluate the impact of the different failure and recovery probabilities over the selection process, a sensitivity analysis is presented. The results show that considering congestion is especially critical for risk-neutral decision makers in mitigating against disruptions.