IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v209y2011i2p156-165.html
   My bibliography  Save this article

Prepositioning supplies in preparation for disasters

Author

Listed:
  • Campbell, Ann Melissa
  • Jones, Philip C.

Abstract

In this paper, we examine the decision of where to preposition supplies in preparation for a disaster, such as a hurricane or terrorist attack, and how much to preposition at a location. If supplies are located closer to the disaster, it can allow for faster delivery of supplies after the disaster. As a result of being closer, though, the supplies may be in a risky location if the disaster occurs. Considering these risks, we derive equations for determining the optimal stocking quantity and the total expected costs associated with delivering to a demand point from a supply point. We provide a sensitivity analysis to show how different parameters impact stocking levels and costs. We show how our cost model can be used to select the single best supply point location from a discrete set of choices and how it can be embedded within existing location algorithms to choose multiple supply points. Our computational experiments involve a variety of relationships between distance and risk and show how these can impact location decisions and stocking levels.

Suggested Citation

  • Campbell, Ann Melissa & Jones, Philip C., 2011. "Prepositioning supplies in preparation for disasters," European Journal of Operational Research, Elsevier, vol. 209(2), pages 156-165, March.
  • Handle: RePEc:eee:ejores:v:209:y:2011:i:2:p:156-165
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(10)00589-8
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mete, Huseyin Onur & Zabinsky, Zelda B., 2010. "Stochastic optimization of medical supply location and distribution in disaster management," International Journal of Production Economics, Elsevier, vol. 126(1), pages 76-84, July.
    2. Jamie Dekle & Mariel S. Lavieri & Erica Martin & Hülya Emir-Farinas & Richard L. Francis, 2005. "A Florida County Locates Disaster Recovery Centers," Interfaces, INFORMS, vol. 35(2), pages 133-139, April.
    3. Mark S. Daskin, 1983. "A Maximum Expected Covering Location Model: Formulation, Properties and Heuristic Solution," Transportation Science, INFORMS, vol. 17(1), pages 48-70, February.
    4. E J Lodree Jr & S Taskin, 2008. "An insurance risk management framework for disaster relief and supply chain disruption inventory planning," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(5), pages 674-684, May.
    5. Margaret L. Brandeau & Samuel S. Chiu, 1989. "An Overview of Representative Problems in Location Research," Management Science, INFORMS, vol. 35(6), pages 645-674, June.
    6. Mozart Menezes & O. Berman & D. Krass, 2007. "Facility Reliability Issues in Network p-Median Problems: Strategic Centralization and Co-location Effects," Post-Print halshs-00170396, HAL.
    7. Lawrence V. Snyder & Mark S. Daskin, 2005. "Reliability Models for Facility Location: The Expected Failure Cost Case," Transportation Science, INFORMS, vol. 39(3), pages 400-416, August.
    Full references (including those not matched with items on IDEAS)

    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. Feng, Keli & Bizimana, Emmanuel & Agu, Deedee D. & Issac, Tana T., 2012. "Optimization and Simulation Modeling of Disaster Relief Supply Chain: A Literature Review," MPRA Paper 58204, University Library of Munich, Germany.
    2. Hasani, Aliakbar & Mokhtari, Hadi, 2018. "Redesign strategies of a comprehensive robust relief network for disaster management," Socio-Economic Planning Sciences, Elsevier, vol. 64(C), pages 92-102.
    3. Ansari, Sina & Başdere, Mehmet & Li, Xiaopeng & Ouyang, Yanfeng & Smilowitz, Karen, 2018. "Advancements in continuous approximation models for logistics and transportation systems: 1996–2016," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 229-252.
    4. O’Hanley, Jesse R. & Scaparra, M. Paola & García, Sergio, 2013. "Probability chains: A general linearization technique for modeling reliability in facility location and related problems," European Journal of Operational Research, Elsevier, vol. 230(1), pages 63-75.
    5. An, Shi & Cui, Na & Bai, Yun & Xie, Weijun & Chen, Mingliu & Ouyang, Yanfeng, 2015. "Reliable emergency service facility location under facility disruption, en-route congestion and in-facility queuing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 82(C), pages 199-216.
    6. Akgün, İbrahim & Gümüşbuğa, Ferhat & Tansel, Barbaros, 2015. "Risk based facility location by using fault tree analysis in disaster management," Omega, Elsevier, vol. 52(C), pages 168-179.
    7. Tingting Cui & Yanfeng Ouyang & Zuo-Jun Max Shen, 2010. "Reliable Facility Location Design Under the Risk of Disruptions," Operations Research, INFORMS, vol. 58(4-part-1), pages 998-1011, August.
    8. Ting L. Lei & Richard L. Church, 2014. "Vector Assignment Ordered Median Problem," International Regional Science Review, , vol. 37(2), pages 194-224, April.
    9. Trung Hieu Tran & Thu Ba T. Nguyen, 2019. "Alternative-fuel station network design under impact of station failures," Annals of Operations Research, Springer, vol. 279(1), pages 151-186, August.
    10. Cui, Tingting & Ouyang, Yanfeng & Shen, Zuo-Jun Max J, 2010. "Reliable Facility Location Design under the Risk of Disruptions," University of California Transportation Center, Working Papers qt5sh2c7pw, University of California Transportation Center.
    11. 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).
    12. Zhi-Chun Li & Qian Liu, 2020. "Optimal deployment of emergency rescue stations in an urban transportation corridor," Transportation, Springer, vol. 47(1), pages 445-473, February.
    13. Prima Denny Sentia & Syaimak Abdul Shukor & Amelia Natasya Abdul Wahab & Muriati Mukhtar, 2023. "Logistic distribution in humanitarian supply chain management: a thematic literature review and future research," Annals of Operations Research, Springer, vol. 323(1), pages 175-201, April.
    14. 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.
    15. Masashi Miyagawa, 2012. "Joint distribution of distances to the first and the second nearest facilities," Journal of Geographical Systems, Springer, vol. 14(2), pages 209-222, April.
    16. Trung Hieu Tran & Jesse R. O’Hanley & M. Paola Scaparra, 2017. "Reliable Hub Network Design: Formulation and Solution Techniques," Transportation Science, INFORMS, vol. 51(1), pages 358-375, February.
    17. Robert Aboolian & Tingting Cui & Zuo-Jun Max Shen, 2013. "An Efficient Approach for Solving Reliable Facility Location Models," INFORMS Journal on Computing, INFORMS, vol. 25(4), pages 720-729, November.
    18. O'Hanley, Jesse R. & Church, Richard L., 2011. "Designing robust coverage networks to hedge against worst-case facility losses," European Journal of Operational Research, Elsevier, vol. 209(1), pages 23-36, February.
    19. Ting Lei & Daoqin Tong, 2013. "Hedging against service disruptions: an expected median location problem with site-dependent failure probabilities," Journal of Geographical Systems, Springer, vol. 15(4), pages 491-512, October.
    20. 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.

    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:eee:ejores:v:209:y:2011:i:2:p:156-165. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.