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A two-period model for selection of resilient multi-tier supply portfolio

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  • Tadeusz Sawik

Abstract

A two-period decision-making model is developed for selection of resilient supply portfolio in a multi-tier supply chain under disruption risks. The planning horizon is divided into two aggregate periods: before and after the disruption. The resilience of the supply chain is achieved by selection ahead of time primary supply portfolio and by pre-positioning of risk mitigation inventory of parts at different tiers that will hedge against all disruption scenarios. Simultaneously, recovery and transshipment portfolios are determined for each disruption scenario and decisions on usage the pre-positioned inventory are made to minimise expected cost or maximise expected service level. Some properties of optimal solutions, derived from the proposed model provide additional managerial insights. The findings also indicate that the developed portfolio approach with an embedded network flow structure leads to computationally efficient stochastic mixed integer program with a strong LP relaxation.

Suggested Citation

  • Tadeusz Sawik, 2020. "A two-period model for selection of resilient multi-tier supply portfolio," International Journal of Production Research, Taylor & Francis Journals, vol. 58(19), pages 6043-6060, October.
  • Handle: RePEc:taf:tprsxx:v:58:y:2020:i:19:p:6043-6060
    DOI: 10.1080/00207543.2019.1665204
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    Cited by:

    1. Aida Rezaei & Amir Aghsami & Masoud Rabbani, 2021. "Supplier selection and order allocation model with disruption and environmental risks in centralized supply chain," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(6), pages 1036-1072, December.
    2. Sawik, Tadeusz, 2022. "Stochastic optimization of supply chain resilience under ripple effect: A COVID-19 pandemic related study," Omega, Elsevier, vol. 109(C).

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