IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i8p4141-d532152.html
   My bibliography  Save this article

Pre-Positioning Facility Location and Resource Allocation in Humanitarian Relief Operations Considering Deprivation Costs

Author

Listed:
  • Linlin Zhang

    (School of Civil Engineering and Architecture, University of Jinan, Jinan 250022, China)

  • Na Cui

    (School of Civil Engineering and Architecture, University of Jinan, Jinan 250022, China)

Abstract

Alleviating human sufferings during and in the aftermath of disasters is one of the most important goals in humanitarian relief logistics. The lack of relief commodities, especially life-saving items, is a life-threatening loss to victims and must be considered when making emergency supply allocation and transportation decisions, even in the pre-disaster prepositioning phase. This paper proposes a scenario-based stochastic program that integrates the decisions of prepositioning facility locations, quantities of stocked emergency supplies, and service allocations in each scenario in the same modeling framework. The estimation of victims’ losses for waiting for emergency supplies is measured in the typical deprivation cost function and treated as one of the main bases of decision making, besides traditional transportation costs, in determining the service allocation strategies in each scenario. Specifically, a case study with data from the hurricane threat in the Gulf Coast area of the US was conducted to demonstrate the application of this model and the significance of considering victims’ welfare loss in humanitarian relief logistics. Some interesting managerial insights were also drawn from a series of numerical experiments and sensitivity analyses.

Suggested Citation

  • Linlin Zhang & Na Cui, 2021. "Pre-Positioning Facility Location and Resource Allocation in Humanitarian Relief Operations Considering Deprivation Costs," Sustainability, MDPI, vol. 13(8), pages 1-26, April.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:8:p:4141-:d:532152
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/8/4141/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/8/4141/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sheu, Jiuh-Biing, 2007. "An emergency logistics distribution approach for quick response to urgent relief demand in disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(6), pages 687-709, November.
    2. Moreno, Alfredo & Alem, Douglas & Ferreira, Deisemara & Clark, Alistair, 2018. "An effective two-stage stochastic multi-trip location-transportation model with social concerns in relief supply chains," European Journal of Operational Research, Elsevier, vol. 269(3), pages 1050-1071.
    3. Cotes, Nathalie & Cantillo, Victor, 2019. "Including deprivation costs in facility location models for humanitarian relief logistics," Socio-Economic Planning Sciences, Elsevier, vol. 65(C), pages 89-100.
    4. Khayal, Danya & Pradhananga, Rojee & Pokharel, Shaligram & Mutlu, Fatih, 2015. "A model for planning locations of temporary distribution facilities for emergency response," Socio-Economic Planning Sciences, Elsevier, vol. 52(C), pages 22-30.
    5. Gutjahr, Walter J. & Fischer, Sophie, 2018. "Equity and deprivation costs in humanitarian logistics," European Journal of Operational Research, Elsevier, vol. 270(1), pages 185-197.
    6. Rawls, Carmen G. & Turnquist, Mark A., 2010. "Pre-positioning of emergency supplies for disaster response," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 521-534, May.
    7. Wenjun Ni & Jia Shu & Miao Song, 2018. "Location and Emergency Inventory Pre†Positioning for Disaster Response Operations: Min†Max Robust Model and a Case Study of Yushu Earthquake," Production and Operations Management, Production and Operations Management Society, vol. 27(1), pages 160-183, January.
    8. An, Shi & Cui, Na & Li, Xiaopeng & Ouyang, Yanfeng, 2013. "Location planning for transit-based evacuation under the risk of service disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 54(C), pages 1-16.
    9. Cantillo, Victor & Serrano, Iván & Macea, Luis F. & Holguín-Veras, José, 2018. "Discrete choice approach for assessing deprivation cost in humanitarian relief operations," Socio-Economic Planning Sciences, Elsevier, vol. 63(C), pages 33-46.
    10. Li Zhu & Yeming Gong & Yishui Xu & Jun Gu, 2019. "Emergency Relief Routing Models for Injured Victims Considering Equity and Priority," Post-Print hal-02312250, HAL.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Huizhu Wang & Jianqin Zhou, 2023. "Location of Railway Emergency Rescue Spots Based on a Near-Full Covering Problem: From a Perspective of Diverse Scenarios," Sustainability, MDPI, vol. 15(8), pages 1-16, April.
    2. Fabiana Santos Lima & Ricardo Villarroel Dávalos & Lucila M. S. Campos & Andréa Cristina Trierweiller, 2022. "Framework proposal to support the suppliers’ selection of Humanitarian assistance items: a Flood Case Study in Brazil," Annals of Operations Research, Springer, vol. 315(1), pages 317-340, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. Li Zhu & Yeming Gong & Yishui Xu & Jun Gu, 2019. "Emergency relief routing models for injured victims considering equity and priority," Annals of Operations Research, Springer, vol. 283(1), pages 1573-1606, December.
    3. Guo, Penghui & Zhu, Jianjun, 2023. "Capacity reservation for humanitarian relief: A logic-based Benders decomposition method with subgradient cut," European Journal of Operational Research, Elsevier, vol. 311(3), pages 942-970.
    4. Kawase, Riki & Iryo, Takamasa, 2023. "Optimal stochastic inventory-distribution strategy for damaged multi-echelon humanitarian logistics network," European Journal of Operational Research, Elsevier, vol. 309(2), pages 616-633.
    5. Cao, Cejun & Liu, Yang & Tang, Ou & Gao, Xuehong, 2021. "A fuzzy bi-level optimization model for multi-period post-disaster relief distribution in sustainable humanitarian supply chains," International Journal of Production Economics, Elsevier, vol. 235(C).
    6. Diehlmann, Florian & Hiemsch, Patrick S. & Wiens, Marcus & Lüttenberg, Markus & Schultmann, Frank, 2020. "A novel approach to include social costs in humanitarian objective functions," Working Paper Series in Production and Energy 52, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    7. Hu, Shaolong & Dong, Zhijie Sasha, 2019. "Supplier selection and pre-positioning strategy in humanitarian relief," Omega, Elsevier, vol. 83(C), pages 287-298.
    8. Jianfang Shao & Changyong Liang & Xihui Wang & Xiang Wang & Liang Liang, 2020. "Relief Demand Calculation in Humanitarian Logistics Using Material Classification," IJERPH, MDPI, vol. 17(2), pages 1-25, January.
    9. 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.
    10. Amir Jamali & Amirhossein Ranjbar & Jafar Heydari & Sina Nayeri, 2022. "A multi-objective stochastic programming model to configure a sustainable humanitarian logistics considering deprivation cost and patient severity," Annals of Operations Research, Springer, vol. 319(1), pages 1265-1300, December.
    11. 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.
    12. 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).
    13. Sun, Huali & Li, Jiamei & Wang, Tingsong & Xue, Yaofeng, 2022. "A novel scenario-based robust bi-objective optimization model for humanitarian logistics network under risk of disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    14. Chowdhury, Sudipta & Emelogu, Adindu & Marufuzzaman, Mohammad & Nurre, Sarah G. & Bian, Linkan, 2017. "Drones for disaster response and relief operations: A continuous approximation model," International Journal of Production Economics, Elsevier, vol. 188(C), pages 167-184.
    15. Loree, Nick & Aros-Vera, Felipe, 2018. "Points of distribution location and inventory management model for Post-Disaster Humanitarian Logistics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 1-24.
    16. Hasti Seraji & Reza Tavakkoli-Moghaddam & Sobhan Asian & Harpreet Kaur, 2022. "An integrative location-allocation model for humanitarian logistics with distributive injustice and dissatisfaction under uncertainty," Annals of Operations Research, Springer, vol. 319(1), pages 211-257, December.
    17. 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.
    18. Yanyan Wang & Vicki M. Bier & Baiqing Sun, 2019. "Measuring and Achieving Equity in Multiperiod Emergency Material Allocation," Risk Analysis, John Wiley & Sons, vol. 39(11), pages 2408-2426, November.
    19. Liu, Kanglin & Zhang, Hengliang & Zhang, Zhi-Hai, 2021. "The efficiency, equity and effectiveness of location strategies in humanitarian logistics: A robust chance-constrained approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    20. Renata Turkeš & Daniel Palhazi Cuervo & Kenneth Sörensen, 2019. "Pre-positioning of emergency supplies: does putting a price on human life help to save lives?," Annals of Operations Research, Springer, vol. 283(1), pages 865-895, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:13:y:2021:i:8:p:4141-:d:532152. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.