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To address long-term supply chain (SC) disruptions caused by COVID-19, this chapter integrates two mitigation strategies: product change and emergency procurement, while incorporating product life cycle (PLC) and design change time. A mixed-integer linear programming (MILP) model is proposed to maximize manufacturer profit, considering backorder compensation, lost sales, and multi-echelon SC structures (suppliers-manufacturer-distribution centers-clients). A two-stage heuristic algorithm solves the model efficiently. Numerical experiments verify that the strategy effectively reduces profit losses by adapting to PLC stages (introduction/growth/maturity) and balancing supply-demand dynamics. Sensitivity analysis confirms robustness to key parameters like change cost and production capacity. This work provides a practical tool for SC resilience under prolonged disruptions.

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Recovery Strategy Considering Product Changes and Life Cycle

  • 章节

  • 发表日期：

    2026年

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

摘要

To address long-term supply chain (SC) disruptions caused by COVID-19, this chapter integrates two mitigation strategies: product change and emergency procurement, while incorporating product life cycle (PLC) and design change time. A mixed-integer linear programming (MILP) model is proposed to maximize manufacturer profit, considering backorder compensation, lost sales, and multi-echelon SC structures (suppliers-manufacturer-distribution centers-clients). A two-stage heuristic algorithm solves the model efficiently. Numerical experiments verify that the strategy effectively reduces profit losses by adapting to PLC stages (introduction/growth/maturity) and balancing supply-demand dynamics. Sensitivity analysis confirms robustness to key parameters like change cost and production capacity. This work provides a practical tool for SC resilience under prolonged disruptions.