IDEAS home Printed from https://ideas.repec.org/p/cdl/itsdav/qt83m87669.html
   My bibliography  Save this paper

Optimal Allocation of Multiple Emergency Service Resources for Protection of Critical Transportation Infrastructure

Author

Listed:
  • Huang, Yongxi
  • Fan, Yueyue
  • Cheu, Ruey Long

Abstract

Optimal deployment of limited emergency resources in a large area is of interest to public agencies at all levels. In this paper, the problem of allocating limited emergency service vehicles including fire engines, fire trucks, and ambulances among a set of candidate stations is formulated as a mixed integer linear programming model, in which the objective is to maximize the service coverage of critical transportation infrastructure (CTI). On the basis of this model, the effects of demand at CTI nodes and of transportation network performance on the optimal coverage of CTI are studied. In addition, given a fixed total budget, the most efficient distribution of investment among the three types of emergency service vehicles is identified. To cope with the uncertainty involved in some of the model parameters such as traffic network performance, formulations based on various risk preferences are proposed. The concept of regret is applied to evaluate the robustness of proposed resource allocation strategies. The applicability of the proposed methodologies to high-density metropolitan areas is demonstrated through a case study that uses data from current practice in Singapore.

Suggested Citation

  • Huang, Yongxi & Fan, Yueyue & Cheu, Ruey Long, 2008. "Optimal Allocation of Multiple Emergency Service Resources for Protection of Critical Transportation Infrastructure," Institute of Transportation Studies, Working Paper Series qt83m87669, Institute of Transportation Studies, UC Davis.
    • Handle: RePEc:cdl:itsdav:qt83m87669
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/83m87669.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Owen, Susan Hesse & Daskin, Mark S., 1998. "Strategic facility location: A review," European Journal of Operational Research, Elsevier, vol. 111(3), pages 423-447, December.
    2. David J. Eaton & Mark S. Daskin & Dennis Simmons & Bill Bulloch & Glen Jansma, 1985. "Determining Emergency Medical Service Vehicle Deployment in Austin, Texas," Interfaces, INFORMS, vol. 15(1), pages 96-108, February.
    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. Khaled Abdelghany & Parya Roustaee & Ahmed Hassan & Aline Karak & Mohammad Khodayar, 2023. "Equilibrium-based Workload Balancing for Robust Emergency Response Operation," Networks and Spatial Economics, Springer, vol. 23(3), pages 715-753, September.

    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. Juan Villegas & Fernando Palacios & Andrés Medaglia, 2006. "Solution methods for the bi-objective (cost-coverage) unconstrained facility location problem with an illustrative example," Annals of Operations Research, Springer, vol. 147(1), pages 109-141, October.
    2. Benneyan, James C. & Musdal, Hande & Ceyhan, Mehmet Erkan & Shiner, Brian & Watts, Bradley V., 2012. "Specialty care single and multi-period location–allocation models within the Veterans Health Administration," Socio-Economic Planning Sciences, Elsevier, vol. 46(2), pages 136-148.
    3. Xueping Li & Zhaoxia Zhao & Xiaoyan Zhu & Tami Wyatt, 2011. "Covering models and optimization techniques for emergency response facility location and planning: a review," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 74(3), pages 281-310, December.
    4. Alan T. Murray, 2016. "Maximal Coverage Location Problem," International Regional Science Review, , vol. 39(1), pages 5-27, January.
    5. Ana Iannoni & Reinaldo Morabito & Cem Saydam, 2008. "A hypercube queueing model embedded into a genetic algorithm for ambulance deployment on highways," Annals of Operations Research, Springer, vol. 157(1), pages 207-224, January.
    6. Batta, Rajan & Lejeune, Miguel & Prasad, Srinivas, 2014. "Public facility location using dispersion, population, and equity criteria," European Journal of Operational Research, Elsevier, vol. 234(3), pages 819-829.
    7. Alfandari, Laurent, 2004. "Choice Rules with Size Constraints for Multiple Criteria Decision Making," ESSEC Working Papers DR 04002, ESSEC Research Center, ESSEC Business School.
    8. Sarhadi, Hassan & Naoum-Sawaya, Joe & Verma, Manish, 2020. "A robust optimization approach to locating and stockpiling marine oil-spill response facilities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    9. Sauvey, Christophe & Melo, Teresa & Correia, Isabel, 2019. "Two-phase heuristics for a multi-period capacitated facility location problem with service-differentiated customers," Technical Reports on Logistics of the Saarland Business School 16, Saarland University of Applied Sciences (htw saar), Saarland Business School.
    10. García Cáceres, Rafael Guillermo & Aráoz Durand, Julián Arturo & Gómez, Fernando Palacios, 2009. "Integral analysis method - IAM," European Journal of Operational Research, Elsevier, vol. 192(3), pages 891-903, February.
    11. P. Daniel Wright & Matthew J. Liberatore & Robert L. Nydick, 2006. "A Survey of Operations Research Models and Applications in Homeland Security," Interfaces, INFORMS, vol. 36(6), pages 514-529, December.
    12. Srinivas, Sharan & Ramachandiran, Surya & Rajendran, Suchithra, 2022. "Autonomous robot-driven deliveries: A review of recent developments and future directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
    13. Lagergren, Marten, 1998. "What is the role and contribution of models to management and research in the health services? A view from Europe," European Journal of Operational Research, Elsevier, vol. 105(2), pages 257-266, March.
    14. Stephanie A. Snyder & Robert G. Haight, 2016. "Application of the Maximal Covering Location Problem to Habitat Reserve Site Selection," International Regional Science Review, , vol. 39(1), pages 28-47, January.
    15. Correia, Isabel & Melo, Teresa, 2016. "A computational comparison of formulations for a multi-period facility location problem with modular capacity adjustments and flexible demand fulfillment," Technical Reports on Logistics of the Saarland Business School 11, Saarland University of Applied Sciences (htw saar), Saarland Business School.
    16. Gang Chen & Mark S. Daskin & Zuo‐Jun Max Shen & Stanislav Uryasev, 2006. "The α‐reliable mean‐excess regret model for stochastic facility location modeling," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(7), pages 617-626, October.
    17. Emde, Simon & Boysen, Nils, 2012. "Optimally locating in-house logistics areas to facilitate JIT-supply of mixed-model assembly lines," International Journal of Production Economics, Elsevier, vol. 135(1), pages 393-402.
    18. Clavijo López, Christian & Crama, Yves & Pironet, Thierry & Semet, Frédéric, 2024. "Multi-period distribution networks with purchase commitment contracts," European Journal of Operational Research, Elsevier, vol. 312(2), pages 556-572.
    19. Laijun Zhao & Huiyong Li & Yan Sun & Rongbing Huang & Qingmi Hu & Jiajia Wang & Fei Gao, 2017. "Planning Emergency Shelters for Urban Disaster Resilience: An Integrated Location-Allocation Modeling Approach," Sustainability, MDPI, vol. 9(11), pages 1-20, November.
    20. Tommy Carpenter & Andrew Curtis & S. Keshav, 2014. "The return on investment for taxi companies transitioning to electric vehicles," Transportation, Springer, vol. 41(4), pages 785-818, July.

    More about this item

    Keywords

    UCD-ITS-RP-08-11;

    Statistics

    Access and download statistics

    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:cdl:itsdav:qt83m87669. 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: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucdus.html .

    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.