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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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    1. A. Charnes & W. W. Cooper & R. O. Ferguson, 1955. "Optimal Estimation of Executive Compensation by Linear Programming," Management Science, INFORMS, vol. 1(2), pages 138-151, January.
    2. Keyvanshokooh, Esmaeil & Ryan, Sarah M. & Kabir, Elnaz, 2016. "Hybrid robust and stochastic optimization for closed-loop supply chain network design using accelerated Benders decomposition," European Journal of Operational Research, Elsevier, vol. 249(1), pages 76-92.
    3. Nooraie, S. Vahid & Mellat Parast, Mahour, 2015. "A multi-objective approach to supply chain risk management: Integrating visibility with supply and demand risk," International Journal of Production Economics, Elsevier, vol. 161(C), pages 192-200.
    4. Altay, Nezih & Green III, Walter G., 2006. "OR/MS research in disaster operations management," European Journal of Operational Research, Elsevier, vol. 175(1), pages 475-493, November.
    5. Jonathan F. Bard, 1984. "Optimality conditions for the bilevel programming problem," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 31(1), pages 13-26, March.
    6. Yu, Min-Chun & Goh, Mark, 2014. "A multi-objective approach to supply chain visibility and risk," European Journal of Operational Research, Elsevier, vol. 233(1), pages 125-130.
    7. Aouni, Belaid & Kettani, Ossama, 2001. "Goal programming model: A glorious history and a promising future," European Journal of Operational Research, Elsevier, vol. 133(2), pages 225-231, January.
    8. Tzeng, Gwo-Hshiung & Cheng, Hsin-Jung & Huang, Tsung Dow, 2007. "Multi-objective optimal planning for designing relief delivery systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 673-686, November.
    9. Herminia I. Calvete & Carmen Galé, 2010. "A Multiobjective Bilevel Program for Production-Distribution Planning in a Supply Chain," Lecture Notes in Economics and Mathematical Systems, in: Matthias Ehrgott & Boris Naujoks & Theodor J. Stewart & Jyrki Wallenius (ed.), Multiple Criteria Decision Making for Sustainable Energy and Transportation Systems, pages 155-165, Springer.
    10. Ben-Tal, Aharon & Chung, Byung Do & Mandala, Supreet Reddy & Yao, Tao, 2011. "Robust optimization for emergency logistics planning: Risk mitigation in humanitarian relief supply chains," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1177-1189, September.
    11. Arora, S.R. & Gupta, Ritu, 2009. "Interactive fuzzy goal programming approach for bilevel programming problem," European Journal of Operational Research, Elsevier, vol. 194(2), pages 368-376, April.
    12. Calvete, Herminia I. & Galé, Carmen & Iranzo, José A., 2014. "Planning of a decentralized distribution network using bilevel optimization," Omega, Elsevier, vol. 49(C), pages 30-41.
    13. Gutjahr, Walter J. & Dzubur, Nada, 2016. "Bi-objective bilevel optimization of distribution center locations considering user equilibria," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 85(C), pages 1-22.
    14. Cheng, Chi-Bin, 2011. "Reverse auction with buyer-supplier negotiation using bi-level distributed programming," European Journal of Operational Research, Elsevier, vol. 211(3), pages 601-611, June.
    15. Safar Fazli & Reza Kiani & Mohammadali Vosooghidizaji, 2015. "Crude oil supply chain risk management with DEMATEL–ANP," Post-Print hal-02327343, HAL.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

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    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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