Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 176-200 |
| Number of pages | 25 |
| Journal | Transportation Research Part E: Logistics and Transportation Review |
| Volume | 101 |
| Early online date | 30 Mar 2017 |
| DOIs | |
| Publication status | Published - 1 May 2017 |
| Externally published | Yes |
Keywords
- Supply chain network design
- Risk management
- Multi-stage stochastic programming
- Scenario reduction
- Mitigation and contingency strategies
- Disruption risk