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Resilience Analysis of Multi-modal Logistics Service Network Through Robust Optimization with Budget-of-Uncertainty

Author

Listed:
  • Yaxin Pang

    (CGS i3)

  • Shenle Pan

    (CGS i3)

  • Eric Ballot

    (CGS i3)

Abstract

Supply chain resilience analysis aims to identify the critical elements in the supply chain, measure its reliability, and analyze solutions for improving vulnerabilities. While extensive methods like stochastic approaches have been dominant, robust optimization-widely applied in robust planning under uncertainties without specific probability distributions-remains relatively underexplored for this research problem. This paper employs robust optimization with budget-of-uncertainty as a tool to analyze the resilience of multi-modal logistics service networks under time uncertainty. We examine the interactive effects of three critical factors: network size, disruption scale, disruption degree. The computational experiments offer valuable managerial insights for practitioners and researchers.

Suggested Citation

  • Yaxin Pang & Shenle Pan & Eric Ballot, 2024. "Resilience Analysis of Multi-modal Logistics Service Network Through Robust Optimization with Budget-of-Uncertainty," Papers 2405.12565, arXiv.org.
    • Handle: RePEc:arx:papers:2405.12565
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    File URL: http://arxiv.org/pdf/2405.12565
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    References listed on IDEAS

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    1. Seyed Mohammad Khalili & Fariborz Jolai & Seyed Ali Torabi, 2017. "Integrated production–distribution planning in two-echelon systems: a resilience view," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 1040-1064, February.
    2. Wu, Yangyang & Chen, Suren, 2023. "Resilience modeling and pre-hazard mitigation planning of transportation network to support post-earthquake emergency medical response," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    3. Crainic, Teodor Gabriel, 2000. "Service network design in freight transportation," European Journal of Operational Research, Elsevier, vol. 122(2), pages 272-288, April.
    4. Dui, Hongyan & Zheng, Xiaoqian & Wu, Shaomin, 2021. "Resilience analysis of maritime transportation systems based on importance measures," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
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