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Emergency logistics planning under supply risk and demand uncertainty

Author

Listed:
  • Abdul Sattar Safaei

    (Babol Noshirvani University of Technology)

  • Saba Farsad

    (Babol Noshirvani University of Technology)

  • Mohammad Mahdi Paydar

    (Babol Noshirvani University of Technology)

Abstract

One of the most important issues in the crisis management is to supply and deliver the correct type and quantity of relief items in a dynamic environment of crisis situations. Current research presented a novel bi-objective bi-level optimization model in order to design an integrated framework for relief logistics operations. The Upper level objectives are to minimize total operational cost and total unsatisfied demand considering the effect of distribution locations of relief supplies. The lower level in the hierarchical decision process, proposes suppliers with lower supply risk. The proposed nonlinear model is reformulated as a single-level linear problem, and for the upper-level decision, the goal programming (GP) approach is employed for the exact solution of the model to minimize deviations from the goals of the bi-objective problem. Finally, a case study of emergency planning for earthquake disaster verifies the performance of the presented model.

Suggested Citation

  • Abdul Sattar Safaei & Saba Farsad & Mohammad Mahdi Paydar, 2020. "Emergency logistics planning under supply risk and demand uncertainty," Operational Research, Springer, vol. 20(3), pages 1437-1460, September.
    • Handle: RePEc:spr:operea:v:20:y:2020:i:3:d:10.1007_s12351-018-0376-3
    DOI: 10.1007/s12351-018-0376-3
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    Cited by:

    1. Fei, Liguo & Wang, Yanqing, 2022. "Demand prediction of emergency materials using case-based reasoning extended by the Dempster-Shafer theory," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    2. Hu, Shaolong & Dong, Zhijie Sasha & Lev, Benjamin, 2022. "Supplier selection in disaster operations management: Review and research gap identification," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    3. Zhongxiu Peng & Cong Wang & Wenqing Xu & Jinsong Zhang, 2022. "Research on Location-Routing Problem of Maritime Emergency Materials Distribution Based on Bi-Level Programming," Mathematics, MDPI, vol. 10(8), pages 1-23, April.
    4. Seyed Babak Ebrahimi & Ehsan Bagheri, 2022. "A multi-objective formulation for the closed-loop plastic supply chain under uncertainty," Operational Research, Springer, vol. 22(5), pages 4725-4768, November.
    5. Sara Rye & Emel Aktas, 2023. "A Rule-Based Predictive Model for Estimating Human Impact Data in Natural Onset Disasters—The Case of a PRED Model," Logistics, MDPI, vol. 7(2), pages 1-24, May.
    6. Wang, Qingyi & Liu, Zhuomeng & Jiang, Peng & Luo, Li, 2022. "A stochastic programming model for emergency supplies pre-positioning, transshipment and procurement in a regional healthcare coalition," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).

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