We address a multi-period supply chain (SC) network design where demands of customers depend on facilities serving them based on their delivery lead-times. Potential customer demands are stochastic, and facilities’ capacity varies randomly because of possible disruptions. Accordingly, we develop a multi-stage stochastic program, and model disruptions’ effect on facilities’ capacity. The SC responsiveness risk is limited and, to obtain a resilient network, both mitigation and contingency strategies are exploited. Computational results on a real-life case study and randomly generated problem instances demonstrate the model’s applicability, risk-measurement policies’ performance, and the influence of mitigation and contingency strategies on SC’s resiliency.
|Number of pages||25|
|Journal||Transportation Research Part E: Logistics and Transportation Review|
|Early online date||30 Mar 2017|
|Publication status||Published - 1 May 2017|