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A bi-objective robust model for emergency resource allocation under uncertainty

Author

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  • C.L. Hu
  • X. Liu
  • Y.K. Hua

Abstract

Emergency resource allocation constitutes one of the most critical elements of response operations in the field of emergency management. This paper addresses an emergency resource allocation problem which involves multiple competing affected areas and one relief resource centre under supply shortage and uncertainty in the post-disaster phase. In humanitarian situations, both the efficiency and fairness of an allocation policy have a considerable influence on the effectiveness of emergency response operations. Thus, we formulate a bi-objective robust emergency resource allocation (BRERA) model which tries to maximise efficiency as well as fairness under different sources of uncertainties. To obtain decision-makers’ most preferred allocation policy, we propose a novel emergency resource allocation decision method which consists of three steps: (1) develop a bi-objective heuristic particle swarm optimisation algorithm to search the Pareto frontier of the BRERA model; (2) select a coefficient to measure fairness; and (3) establish a decision method based on decision-makers’ preference restricted by the fairness coefficient. Finally, a real case study taken from the 5 December 2008 Wenchuan Earthquake demonstrates the effectiveness of the proposed method through numerical results. The solution and model robustness are also analysed.

Suggested Citation

  • C.L. Hu & X. Liu & Y.K. Hua, 2016. "A bi-objective robust model for emergency resource allocation under uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 54(24), pages 7421-7438, December.
  • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:24:p:7421-7438
    DOI: 10.1080/00207543.2016.1191692
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    Cited by:

    1. Masoud Mahootchi & Sajjad Golmohammadi, 2018. "Developing a new stochastic model considering bi-directional relations in a natural disaster: a possible earthquake in Tehran (the Capital of Islamic Republic of Iran)," Annals of Operations Research, Springer, vol. 269(1), pages 439-473, October.
    2. Li, Linda & Firouz, Mohammad & Ahmed, Abdulaziz & Delen, Dursun, 2023. "On the Egalitarian–Utilitarian spectrum in stochastic capacitated resource allocation problems," International Journal of Production Economics, Elsevier, vol. 262(C).
    3. Donghai Wang & Menghao Xi & Yingzhen Chen, 2020. "A Dynamic Shelter Location and Victim Resettlement Model Considering Equitable Waiting Costs," IJERPH, MDPI, vol. 17(2), pages 1-17, January.
    4. Balcik, Burcu & Yanıkoğlu, İhsan, 2020. "A robust optimization approach for humanitarian needs assessment planning under travel time uncertainty," European Journal of Operational Research, Elsevier, vol. 282(1), pages 40-57.
    5. Yang, Yongjian & Yin, Yunqiang & Wang, Dujuan & Ignatius, Joshua & Cheng, T.C.E. & Dhamotharan, Lalitha, 2023. "Distributionally robust multi-period location-allocation with multiple resources and capacity levels in humanitarian logistics," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1042-1062.
    6. Xuehong Gao, 2022. "A bi-level stochastic optimization model for multi-commodity rebalancing under uncertainty in disaster response," Annals of Operations Research, Springer, vol. 319(1), pages 115-148, December.
    7. Ghazaleh Ahmadi & Reza Tavakkoli-Moghaddam & Armand Baboli & Mehdi Najafi, 2022. "A decision support model for robust allocation and routing of search and rescue resources after earthquake: a case study," Operational Research, Springer, vol. 22(2), pages 1039-1081, April.
    8. Zhang, Lingye & Lu, Jing & Yang, Zaili, 2021. "Optimal scheduling of emergency resources for major maritime oil spills considering time-varying demand and transportation networks," European Journal of Operational Research, Elsevier, vol. 293(2), pages 529-546.
    9. Xiang, Xi & Liu, Changchun & Miao, Lixin, 2017. "A bi-objective robust model for berth allocation scheduling under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 294-319.
    10. Seyed Reza Abazari & Fariborz Jolai & Amir Aghsami, 2022. "Designing a humanitarian relief network considering governmental and non-governmental operations under uncertainty," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(3), pages 1430-1452, June.
    11. Baharmand, Hossein & Comes, Tina & Lauras, Matthieu, 2019. "Bi-objective multi-layer location–allocation model for the immediate aftermath of sudden-onset disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 86-110.
    12. R. K. Jana & Chandra Prakash Chandra & Aviral Kumar Tiwari, 2019. "Humanitarian aid delivery decisions during the early recovery phase of disaster using a discrete choice multi-attribute value method," Annals of Operations Research, Springer, vol. 283(1), pages 1211-1225, December.
    13. Qingwen Li & Jiuhe Wang & Yinggang Wang & Jian Lv, 2022. "A Two-Stage Stochastic Programming Model for Emergency Supplies Pre-Position under the Background of Civil-Military Integration," Sustainability, MDPI, vol. 14(19), pages 1-21, September.

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