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Computing Optimal Mitigation Plans for Force-Majeure Scenarios in Dynamic Manufacturing Chains

Author

Listed:
  • Heiner Ackermann

    (Fraunhofer Institute for Industrial Mathematics ITWM)

  • Erik Diessel

    (Fraunhofer Institute for Industrial Mathematics ITWM)

  • Michael Helmling

    (Fraunhofer Institute for Industrial Mathematics ITWM)

  • Neil Jami

    (Fraunhofer Institute for Industrial Mathematics ITWM)

  • Johanna Münch

    (Fraunhofer Institute for Industrial Mathematics ITWM)

Abstract

We consider force-majeure supply disruptions in a dynamic, multi-product manufacturing supply chain with time-dependent parameters. We present a linear programming model that captures a specific force-majeure scenario with respect to several objective functions that can be combined in a multi-objective framework, e.g., minimization of loss, maximization of shortage-free time, or prioritization of mitigation types. Solving this model yields an optimal mitigation plan that describes how to best (re-)allocate supply and production operations. Supported mitigation options include plant-side safety stock, supplier-side inventories, and additional production thus reflecting the manufacturing setting of a large-scale industrial player. We describe a workflow for increasing the resilience of supply chains based on risk profiles generated by our approach.

Suggested Citation

  • Heiner Ackermann & Erik Diessel & Michael Helmling & Neil Jami & Johanna Münch, 2024. "Computing Optimal Mitigation Plans for Force-Majeure Scenarios in Dynamic Manufacturing Chains," SN Operations Research Forum, Springer, vol. 5(2), pages 1-35, June.
    • Handle: RePEc:spr:snopef:v:5:y:2024:i:2:d:10.1007_s43069-024-00333-9
    DOI: 10.1007/s43069-024-00333-9
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    References listed on IDEAS

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