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This chapter addresses SC resilience under long-term disruptions caused by the COVID-19 pandemic, where concurrent supply and production disruptions exhibit time-varying capacity reductions. A modified multi-portfolio approach integrating simulation and predictions is proposed to concurrently select primary and recovery supply and production portfolios. Time-dependent mixed integer programming models incorporating preparedness and recovery measures are developed, solved via a novel prediction-based decomposition optimisation method. Computational experiments on a real-world electronics SC demonstrate the effectiveness of the proposed approach in enhancing SC resilience and viability.

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Recovery Strategy Through Decomposition-Based Optimization

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  • 发表日期：

    2026年

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  • Chen Peng,
  • Hongfeng Wang,
  • Yi Yang,
  • Yong Zhang

摘要

This chapter addresses SC resilience under long-term disruptions caused by the COVID-19 pandemic, where concurrent supply and production disruptions exhibit time-varying capacity reductions. A modified multi-portfolio approach integrating simulation and predictions is proposed to concurrently select primary and recovery supply and production portfolios. Time-dependent mixed integer programming models incorporating preparedness and recovery measures are developed, solved via a novel prediction-based decomposition optimisation method. Computational experiments on a real-world electronics SC demonstrate the effectiveness of the proposed approach in enhancing SC resilience and viability.