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Dynamic Collaborative Optimization for Disaster Relief Supply Chains under Information Ambiguity

Author

Listed:
  • J. Zhu
  • Y. Shi
  • V.G. Venkatesh

    (Métis Lab EM Normandie - EM Normandie - École de Management de Normandie)

  • S. Islam
  • Z. Hou
  • S. Arisian

Abstract

Large-scale disasters occur worldwide, with a continuing surge in the frequency and severity of disruptive events. Researchers have developed several optimization models to address the critical challenges of disaster relief supply chains (e.g., emergency material reserving and scheduling inefficiencies). However, most developed algorithms are proven to have low fault tolerance, which makes it difficult for disaster relief supply chain managers to obtain optimal solutions and meet the emergency distribution requirements within a limited time frame. Considering the uncertainty and ambiguity of disaster relief information and using Interval Type-2 Fuzzy Set (IT2TFS), this paper presents a collaborative optimization model based on an integrative emergency material supplier evaluation framework. The optimal emergency material suppliers are first selected using a multi-attribute group decision-making ranking method. Multi-objective fuzzy optimization is then run in three emergency phases: early -, mid-, and late-disaster relief stages. Focusing on a massive flash flood disaster event in Yunnan Province as a case study, a comprehensive numerical analysis tests and validates the developed model. The results revealed that the proposed optimization method can optimize emergency material planning while ensuring that reserve material safety inventory is always maintained at a reasonable level. The presented method suggests a fuzzy interval to prevent emergency materials' safety inventory shortage and minimize continuous life/property losses in disaster-affected areas. \textcopyright 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Suggested Citation

  • J. Zhu & Y. Shi & V.G. Venkatesh & S. Islam & Z. Hou & S. Arisian, 2022. "Dynamic Collaborative Optimization for Disaster Relief Supply Chains under Information Ambiguity," Post-Print hal-04444816, HAL.
    • Handle: RePEc:hal:journl:hal-04444816
    DOI: 10.1007/s10479-022-04758-5
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    Citations

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    Cited by:

    1. Gang Wang, 2024. "Disaster relief supply chain network planning under uncertainty," Annals of Operations Research, Springer, vol. 338(2), pages 1127-1156, July.
    2. Afshin Kamyabniya & Antoine Sauré & F. Sibel Salman & Noureddine Bénichou & Jonathan Patrick, 2024. "Optimization models for disaster response operations: a literature review," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 46(3), pages 737-783, September.
    3. Liu, Liyi & Tu, Yan & Zhang, Wen & Shen, Wenjing, 2024. "Supplier selection for emergency material based on group exponential TODIM method considering hesitant fuzzy linguistic set: A case study of China," Socio-Economic Planning Sciences, Elsevier, vol. 94(C).

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