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Stochastic optimisation model for integrated decisions on relief supply chains: preparedness for disaster response

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  • Wapee Manopiniwes
  • Takashi Irohara

Abstract

This paper proposes a stochastic linear mixed-integer programming model for integrated decisions in the preparedness and response stages in pre- and post-disaster operations, respectively. We develop a model for integrated decisions that considers three key areas of emergency logistics: facility and stock prepositioning, evacuation planning and relief vehicle planning. To develop a framework for effective relief operations, we consider not only a cost-based but also an equity-based solution approach in our multiple objectives model. Then a normalised weighted sum method is used to parameterise our multiple objective programming model. This paper suggests a compromise between the cost, and the equity of relief victims. The experiments also demonstrate how time restrictions and the availability of relief vehicles impact the two objective functions.

Suggested Citation

  • Wapee Manopiniwes & Takashi Irohara, 2017. "Stochastic optimisation model for integrated decisions on relief supply chains: preparedness for disaster response," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 979-996, February.
    • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:4:p:979-996
    DOI: 10.1080/00207543.2016.1211340
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    Cited by:

    1. Faraz Salehi & Masoud Mahootchi & Seyed Mohammad Moattar Husseini, 2019. "Developing a robust stochastic model for designing a blood supply chain network in a crisis: a possible earthquake in Tehran," Annals of Operations Research, Springer, vol. 283(1), pages 679-703, December.
    2. Abazari, Seyed Reza & Aghsami, Amir & Rabbani, Masoud, 2021. "Prepositioning and distributing relief items in humanitarian logistics with uncertain parameters," Socio-Economic Planning Sciences, Elsevier, vol. 74(C).
    3. Jamal Al Qundus & Kosai Dabbour & Shivam Gupta & Régis Meissonier & Adrian Paschke, 2022. "Wireless sensor network for AI-based flood disaster detection," Annals of Operations Research, Springer, vol. 319(1), pages 697-719, December.
    4. Sara Cheraghi & Seyyed-Mahdi Hosseini-Motlagh, 2020. "Responsive and reliable injured-oriented blood supply chain for disaster relief: a real case study," Annals of Operations Research, Springer, vol. 291(1), pages 129-167, August.
    5. Rodríguez-Espíndola, Oscar & Ahmadi, Hossein & Gastélum-Chavira, Diego & Ahumada-Valenzuela, Omar & Chowdhury, Soumyadeb & Dey, Prasanta Kumar & Albores, Pavel, 2023. "Humanitarian logistics optimization models: An investigation of decision-maker involvement and directions to promote implementation," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    6. Zeinab Sazvar & Mahsa Zokaee & Reza Tavakkoli-Moghaddam & Samira Al-sadat Salari & Sina Nayeri, 2022. "Designing a sustainable closed-loop pharmaceutical supply chain in a competitive market considering demand uncertainty, manufacturer’s brand and waste management," Annals of Operations Research, Springer, vol. 315(2), pages 2057-2088, August.
    7. Fang Xu & Yifan Ma & Chang Liu & Ying Ji, 2024. "Emergency Logistics Facilities Location Dual-Objective Modeling in Uncertain Environments," Sustainability, MDPI, vol. 16(4), pages 1-34, February.
    8. Xuehong Gao, 2019. "A Novel Reverse Logistics Network Design Considering Multi-Level Investments for Facility Reconstruction with Environmental Considerations," Sustainability, MDPI, vol. 11(9), pages 1-22, May.
    9. Dönmez, Zehranaz & Kara, Bahar Y. & Karsu, Özlem & Saldanha-da-Gama, Francisco, 2021. "Humanitarian facility location under uncertainty: Critical review and future prospects," Omega, Elsevier, vol. 102(C).
    10. Hongbin Liu & Guopeng Song & Tianyu Liu & Bo Guo, 2022. "Multitask Emergency Logistics Planning under Multimodal Transportation," Mathematics, MDPI, vol. 10(19), pages 1-25, October.
    11. Sabbaghtorkan, Monir & Batta, Rajan & He, Qing, 2020. "Prepositioning of assets and supplies in disaster operations management: Review and research gap identification," European Journal of Operational Research, Elsevier, vol. 284(1), pages 1-19.
    12. Khanchehzarrin, Saeed & Ghaebi Panah, Mona & Mahdavi-Amiri, Nezam & Shiripour, Saber, 2022. "A bi-level multi-objective location-routing optimization model for disaster relief operations considering public donations," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    13. Shuanglin Li & Kok Lay Teo, 2019. "Post-disaster multi-period road network repair: work scheduling and relief logistics optimization," Annals of Operations Research, Springer, vol. 283(1), pages 1345-1385, December.
    14. Raquel Sanchis & Alfonso Duran-Heras & Raul Poler, 2020. "Optimising the Preparedness Capacity of Enterprise Resilience Using Mathematical Programming," Mathematics, MDPI, vol. 8(9), pages 1-29, September.
    15. Aghajani, Mojtaba & Torabi, S. Ali & Heydari, Jafar, 2020. "A novel option contract integrated with supplier selection and inventory prepositioning for humanitarian relief supply chains," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    16. Rabin K. Jana & Dinesh K. Sharma & Peeyush Mehta, 2022. "A probabilistic fuzzy goal programming model for managing the supply of emergency relief materials," Annals of Operations Research, Springer, vol. 319(1), pages 149-172, December.
    17. Rodolfo Modrigais Strauss Nunes & Susana Carla Farias Pereira, 2022. "Intellectual structure and trends in the humanitarian operations field," Annals of Operations Research, Springer, vol. 319(1), pages 1099-1157, December.
    18. Sohrabi, Mahnaz & Zandieh, Mostafa & Shokouhifar, Mohammad, 2023. "Sustainable inventory management in blood banks considering health equity using a combined metaheuristic-based robust fuzzy stochastic programming," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    19. Wapee Manopiniwes & Takashi Irohara, 2021. "Optimization model for temporary depot problem in flood disaster response," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(2), pages 1743-1763, January.
    20. 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.
    21. 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.
    22. Ali Torabi, S. & Shokr, Iman & Tofighi, Saeideh & Heydari, Jafar, 2018. "Integrated relief pre-positioning and procurement planning in humanitarian supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 113(C), pages 123-146.
    23. 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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