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Robust and reliable medical services network design under uncertain environment and system disruptions

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  • Shishebori, Davood
  • Yousefi Babadi, Abolghasem

Abstract

This paper addresses an efficient mixed integer linear programming model for a robust and reliable medical service (MS) center location network design problem (RR/MSL/NDP), which simultaneously takes uncertain parameters, system disruptions, and investment budget constraint into account. The proposed model is formulated based on an efficient robust optimization approach to protect the network against uncertainty. Furthermore, a mixed integer linear programming model with augmented PR-robust constraints is proposed to control the system reliability under unforeseen situations. A practical case study is presented in detail to illustrate the application of the proposed model.

Suggested Citation

  • Shishebori, Davood & Yousefi Babadi, Abolghasem, 2015. "Robust and reliable medical services network design under uncertain environment and system disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 268-288.
    • Handle: RePEc:eee:transe:v:77:y:2015:i:c:p:268-288
    DOI: 10.1016/j.tre.2015.02.014
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    3. Donya Rahmani, 2019. "Designing a robust and dynamic network for the emergency blood supply chain with the risk of disruptions," Annals of Operations Research, Springer, vol. 283(1), pages 613-641, December.
    4. Zhang, Sizhe & Cardin, Michel-Alexandre, 2017. "Flexibility and real options analysis in emergency medical services systems using decision rules and multi-stage stochastic programming," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 107(C), pages 120-140.
    5. Bhuiyan, Tanveer Hossain & Medal, Hugh R. & Harun, Sarah, 2020. "A stochastic programming model with endogenous and exogenous uncertainty for reliable network design under random disruption," European Journal of Operational Research, Elsevier, vol. 285(2), pages 670-694.
    6. Shaojian Qu & Yefan Han & Zhong Wu & Hassan Raza, 2021. "Consensus Modeling with Asymmetric Cost Based on Data-Driven Robust Optimization," Group Decision and Negotiation, Springer, vol. 30(6), pages 1395-1432, December.
    7. Riccardo Aldrighetti & Ilenia Zennaro & Serena Finco & Daria Battini, 2019. "Healthcare Supply Chain Simulation with Disruption Considerations: A Case Study from Northern Italy," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 20(1), pages 81-102, December.
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    19. Liming Yao & Zhongwen Xu & Ziqiang Zeng, 2020. "A Soft‐Path Solution to Risk Reduction by Modeling Medical Waste Disposal Center Location‐Allocation Optimization," Risk Analysis, John Wiley & Sons, vol. 40(9), pages 1863-1886, September.
    20. Ghaderi, Abdolsalam & Burdett, Robert L., 2019. "An integrated location and routing approach for transporting hazardous materials in a bi-modal transportation network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 49-65.
    21. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry & Zennaro, Ilenia, 2021. "Costs of resilience and disruptions in supply chain network design models: A review and future research directions," International Journal of Production Economics, Elsevier, vol. 235(C).

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