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A robust optimization approach for decontamination planning of emergency planning zone: Facility location and assignment plan

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  • Ji, Ya-Min
  • Qi, Ming-Liang

Abstract

Establishing a robust facility location and assignment plan to improve the efficiency of the decontamination process is critical to alleviating the physical impact of the radiation leakage that occurs in a nuclear accident. This study develops an approach for optimizing the locations of decontamination facilities and assignments of affected villages. The approach is a robust optimization model that optimizes the worst-case performance. The system dynamic model is integrated into the robust optimization model to simulate the decontamination process and compute the decontamination time. A case study is conducted of the Plume Emergency Planning Zone in China. The results indicate that (1) a decontamination site location plan can be obtained in which each site is located in a different direction, (2) no evacuee will be allowed to travel across the downwind area in an assignment plan, and (3) a larger financial investment does not imply an increased decontamination efficiency. An appropriate budget exists that can balance the decontamination time and cost. The proposed model can assist decision makers in (i) better understanding the effects of decontamination site location and village assignment and (ii) deciding which location and assignment plans should be applied to cope with disruptive nuclear accidents.

Suggested Citation

  • Ji, Ya-Min & Qi, Ming-Liang, 2020. "A robust optimization approach for decontamination planning of emergency planning zone: Facility location and assignment plan," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    • Handle: RePEc:eee:soceps:v:70:y:2020:i:c:s0038012118304099
    DOI: 10.1016/j.seps.2019.100740
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    References listed on IDEAS

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    1. Gülpınar, Nalan & Pachamanova, Dessislava & Çanakoğlu, Ethem, 2013. "Robust strategies for facility location under uncertainty," European Journal of Operational Research, Elsevier, vol. 225(1), pages 21-35.
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    4. Jomon Paul & Govind Hariharan, 2012. "Location-allocation planning of stockpiles for effective disaster mitigation," Annals of Operations Research, Springer, vol. 196(1), pages 469-490, July.
    5. ReVelle, C.S. & Eiselt, H.A. & Daskin, M.S., 2008. "A bibliography for some fundamental problem categories in discrete location science," European Journal of Operational Research, Elsevier, vol. 184(3), pages 817-848, February.
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    Cited by:

    1. Sun, Huiping & Li, Yuchen & Zhang, Jianghua, 2022. "Collaboration-based reliable optimal casualty evacuation network design for large-scale emergency preparedness," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    2. Tereza Sedlářová Nehézová & Michal Škoda & Robert Hlavatý & Helena Brožová, 2022. "Fuzzy and robust approach for decision-making in disaster situations," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 617-645, June.

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