Mitigating supply chain disruptions through the assessment of trade-offs among risks, costs and investments in capabilities

One of the central questions in supply chain design is how to properly invest in supply chain capabilities in order to be more responsive to supply chain disruptions. This new perspective in supply chain design requires an understanding of the relationships among costs, supply chain risk drivers, and investments in supply chain capabilities. In this paper, we develop a multi-objective stochastic model for supply chain design under uncertainty and time-dependency. Sources of risk are modeled as a set of scenarios, and the risk of the system is determined. The objective is to examine the trade-offs among investments in improving supply chain capabilities and reducing supply chain risks, and to minimize cost of supply chain disruptions. Due to the NP-hard nature of the problem, a heuristic algorithm based on a relaxation method is designed to determine an optimal or near-optimal solution. To examine the efficiency of the heuristic algorithm, a numerical example is provided. Our findings suggest that increasing supply chain capabilities can be viewed as a mitigation strategy that enables a firm to reduce the total expected cost of a supply chain subject to disruptions.