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 |
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Journal | Transportation Research Part E: Logistics and Transportation Review |
Volume | 101 |
Pages (from-to) | 176-200 |
ISSN | 1366-5545 |
DOIs | |
Publication status | Published - 2017 |
Keywords
- Disruption risk
- Mitigation and contingency strategies
- Multi-stage stochastic programming
- Risk management
- Scenario reduction
- Supply chain network design