IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v309y2023i3p1237-1262.html
   My bibliography  Save this article

Simulation optimization for stochastic casualty collection point location and resource allocation problem in a mass casualty incident

Author

Listed:
  • Chang, Kuo-Hao
  • Chen, Tzu-Li
  • Yang, Fu-Hao
  • Chang, Tzu-Yin

Abstract

After a severe disaster strikes, a large number of casualties in need of urgent treatment, known as a mass casualty incident (MCI) event, arise from multiple disaster areas in a very short period of time and overwhelm available resources of the local healthcare system. This paper focuses on the effective design of casualty collection point (CCP) locations and the efficient allocation of limited emergency medical service (EMS) resources to transport casualties quickly to appropriate hospitals and increase the survival rate of casualties. A hybrid simulation–optimization approach to optimize the CCP location and EMS resource allocation problem over mixed binary and integer feasible domains for the minimization of expected complete delivery time of all casualties from disaster region to hospitals is presented in this work due to the stochastic and dynamic nature of the MCI logistics environment. A high-resolution stochastic discrete event simulation model considering time-varying stochastic casualty arrivals, random triage service times, and stochastic travel times caused by road network vulnerability is first constructed to describe a more detailed modeling of comprehensive MCI humanitarian logistics from the disaster regions to the hospitals. Then, a novel two-stage sequential algorithm, namely a combination of optimal computing budget allocation-based rapid-screening algorithm and adaptive particle global and hyperbox local search (ORSA-APGHLS), is developed to speed up convergence to near-optimal solutions compared to three common existing algorithms (Genetic Algorithm, Tabu Search and Stochastic Nelder-Mead Algorithm) under a limited simulation budget. We collaborate with the National Science and Technology Center for Disaster Reduction (NCDR) in Taiwan to conduct computational experiments to demonstrate the efficiency and efficacy of the proposed two-stage ORSA-APGHLS algorithm according to a potential earthquake scenario occurring in Tainan City, Taiwan. Through sensitivity analysis, the influence of different levels of scarce emergency medical resources and degrees of road damage on the expected complete delivery time of all casualties and the location-allocation decisions are investigated.

Suggested Citation

  • Chang, Kuo-Hao & Chen, Tzu-Li & Yang, Fu-Hao & Chang, Tzu-Yin, 2023. "Simulation optimization for stochastic casualty collection point location and resource allocation problem in a mass casualty incident," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1237-1262.
    • Handle: RePEc:eee:ejores:v:309:y:2023:i:3:p:1237-1262
    DOI: 10.1016/j.ejor.2023.01.065
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221723001121
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2023.01.065?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Shing Chih Tsai, 2013. "Rapid Screening Procedures for Zero-One Optimization via Simulation," INFORMS Journal on Computing, INFORMS, vol. 25(2), pages 317-331, May.
    2. Chang, Kuo-Hao & Hsiung, Tzu-Yi & Chang, Tzu-Yin, 2022. "Multi-Commodity distribution under uncertainty in disaster response phase: Model, solution method, and an empirical study," European Journal of Operational Research, Elsevier, vol. 303(2), pages 857-876.
    3. Elifcan Yaşa & Dilek Tüzün Aksu & Linet Özdamar, 2022. "Metaheuristics for the stochastic post-disaster debris clearance problem," IISE Transactions, Taylor & Francis Journals, vol. 54(10), pages 1004-1017, July.
    4. Vedat Bayram & Hande Yaman, 2018. "Shelter Location and Evacuation Route Assignment Under Uncertainty: A Benders Decomposition Approach," Transportation Science, INFORMS, vol. 52(2), pages 416-436, March.
    5. Aruna Apte & Curtis Heidtke & Javier Salmerón, 2015. "Casualty Collection Points Optimization: A Study for the District of Columbia," Interfaces, INFORMS, vol. 45(2), pages 149-165, April.
    6. Bélanger, V. & Lanzarone, E. & Nicoletta, V. & Ruiz, A. & Soriano, P., 2020. "A recursive simulation-optimization framework for the ambulance location and dispatching problem," European Journal of Operational Research, Elsevier, vol. 286(2), pages 713-725.
    7. Michael C. Fu, 2002. "Feature Article: Optimization for simulation: Theory vs. Practice," INFORMS Journal on Computing, INFORMS, vol. 14(3), pages 192-215, August.
    8. Y. Kergosien & V. Bélanger & P. Soriano & M. Gendreau & A. Ruiz, 2015. "A generic and flexible simulation-based analysis tool for EMS management," International Journal of Production Research, Taylor & Francis Journals, vol. 53(24), pages 7299-7316, December.
    9. Satyajith Amaran & Nikolaos V. Sahinidis & Bikram Sharda & Scott J. Bury, 2016. "Simulation optimization: a review of algorithms and applications," Annals of Operations Research, Springer, vol. 240(1), pages 351-380, May.
    10. T Drezner & Z Drezner & S Salhi, 2006. "A multi-objective heuristic approach for the casualty collection points location problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(6), pages 727-734, June.
    11. Caunhye, Aakil M. & Li, Mingzhe & Nie, Xiaofeng, 2015. "A location-allocation model for casualty response planning during catastrophic radiological incidents," Socio-Economic Planning Sciences, Elsevier, vol. 50(C), pages 32-44.
    12. Zied Jemai & L. Aboueljinane & E. Sahin, 2013. "A review on simulation models applied to emergency medical service operations," Post-Print hal-01672393, HAL.
    13. Farahani, Reza Zanjirani & Lotfi, M.M. & Baghaian, Atefe & Ruiz, Rubén & Rezapour, Shabnam, 2020. "Mass casualty management in disaster scene: A systematic review of OR&MS research in humanitarian operations," European Journal of Operational Research, Elsevier, vol. 287(3), pages 787-819.
    14. Caunhye, Aakil M. & Nie, Xiaofeng & Pokharel, Shaligram, 2012. "Optimization models in emergency logistics: A literature review," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 4-13.
    15. Alizadeh, Morteza & Amiri-Aref, Mehdi & Mustafee, Navonil & Matilal, Sumohon, 2019. "A robust stochastic Casualty Collection Points location problem," European Journal of Operational Research, Elsevier, vol. 279(3), pages 965-983.
    16. 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).
    17. Aakil M. Caunhye & Xiaofeng Nie, 2018. "A Stochastic Programming Model for Casualty Response Planning During Catastrophic Health Events," Transportation Science, INFORMS, vol. 52(2), pages 437-453, March.
    18. Muhammet Gul & Ali Fuat Guneri & Murat M. Gunal, 2020. "Emergency department network under disaster conditions: The case of possible major Istanbul earthquake," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(5), pages 733-747, May.
    19. Li, Yuchen & Zhang, Jianghua & Yu, Guodong, 2020. "A scenario-based hybrid robust and stochastic approach for joint planning of relief logistics and casualty distribution considering secondary disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    20. L. Jeff Hong & Barry L. Nelson, 2006. "Discrete Optimization via Simulation Using COMPASS," Operations Research, INFORMS, vol. 54(1), pages 115-129, February.
    21. Liu, Yang & Cui, Na & Zhang, Jianghua, 2019. "Integrated temporary facility location and casualty allocation planning for post-disaster humanitarian medical service," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 1-16.
    22. Seyed Ali MirHassani & Fatemeh Garmroudi & Farnaz Hooshmand, 2022. "Modeling and solution algorithm for a disaster management problem based on Benders decomposition," IISE Transactions, Taylor & Francis Journals, vol. 54(12), pages 1161-1171, September.
    23. Chang, Kuo-Hao & Cuckler, Robert & Lee, Song-Lin & Lee, Loo Hay, 2022. "Discrete conditional-expectation-based simulation optimization: Methodology and applications," European Journal of Operational Research, Elsevier, vol. 298(1), pages 213-228.
    24. Jie Xu & Barry L. Nelson & L. Jeff Hong, 2013. "An Adaptive Hyperbox Algorithm for High-Dimensional Discrete Optimization via Simulation Problems," INFORMS Journal on Computing, INFORMS, vol. 25(1), pages 133-146, February.
    25. Chang, Kuo-Hao, 2012. "Stochastic Nelder–Mead simplex method – A new globally convergent direct search method for simulation optimization," European Journal of Operational Research, Elsevier, vol. 220(3), pages 684-694.
    26. Dean, Matthew D. & Nair, Suresh K., 2014. "Mass-casualty triage: Distribution of victims to multiple hospitals using the SAVE model," European Journal of Operational Research, Elsevier, vol. 238(1), pages 363-373.
    27. Rongbing Huang & Seokjin Kim & Mozart Menezes, 2010. "Facility location for large-scale emergencies," Annals of Operations Research, Springer, vol. 181(1), pages 271-286, December.
    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. Hongyan Dui & Yulu Zhang & Songru Zhang & Yun-An Zhang, 2023. "Recovery Model and Maintenance Optimization for Urban Road Networks with Congestion," Mathematics, MDPI, vol. 11(9), pages 1-17, April.
    2. Yang, Hengfei & Yang, Yuze & Wang, Dujuan & Cheng, T.C.E. & Yin, Yunqiang & Hu, Hai, 2024. "A scenario-based robust approach for joint planning of multi-blood product logistics and multi-casualty type evacuation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).

    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. Sun, Huiping & Li, Yuchen & Zhang, Jianghua, 2022. "Collaboration-based reliable optimal casualty evacuation network design for large-scale emergency preparedness," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    2. Farahani, Reza Zanjirani & Lotfi, M.M. & Baghaian, Atefe & Ruiz, Rubén & Rezapour, Shabnam, 2020. "Mass casualty management in disaster scene: A systematic review of OR&MS research in humanitarian operations," European Journal of Operational Research, Elsevier, vol. 287(3), pages 787-819.
    3. Atefe Baghaian & M. M. Lotfi & Shabnam Rezapour, 2022. "Integrated deployment of local urban relief teams in the first hours after mass casualty incidents," Operational Research, Springer, vol. 22(4), pages 4517-4555, September.
    4. Zhang, Guowei & Zhu, Ning & Ma, Shoufeng & Xia, Jun, 2021. "Humanitarian relief network assessment using collaborative truck-and-drone system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    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. Satyajith Amaran & Nikolaos V. Sahinidis & Bikram Sharda & Scott J. Bury, 2016. "Simulation optimization: a review of algorithms and applications," Annals of Operations Research, Springer, vol. 240(1), pages 351-380, May.
    7. 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).
    8. 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).
    9. Liu, Yang & Cui, Na & Zhang, Jianghua, 2019. "Integrated temporary facility location and casualty allocation planning for post-disaster humanitarian medical service," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 1-16.
    10. Li, Yuchen & Zhang, Jianghua & Yu, Guodong, 2020. "A scenario-based hybrid robust and stochastic approach for joint planning of relief logistics and casualty distribution considering secondary disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    11. Wang, Jing & Cai, Jianping & Yue, Xiaohang & Suresh, Nallan C., 2021. "Pre-positioning and real-time disaster response operations: Optimization with mobile phone location data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
    12. Chou, Chang-Chi & Chiang, Wen-Chu & Chen, Albert Y., 2022. "Emergency medical response in mass casualty incidents considering the traffic congestions in proximity on-site and hospital delays," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    13. Aakil M. Caunhye & Xiaofeng Nie, 2018. "A Stochastic Programming Model for Casualty Response Planning During Catastrophic Health Events," Transportation Science, INFORMS, vol. 52(2), pages 437-453, March.
    14. Jia, Shuai & Li, Chung-Lun & Xu, Zhou, 2020. "A simulation optimization method for deep-sea vessel berth planning and feeder arrival scheduling at a container port," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 174-196.
    15. Zhang, Guowei & Jia, Ning & Zhu, Ning & Adulyasak, Yossiri & Ma, Shoufeng, 2023. "Robust drone selective routing in humanitarian transportation network assessment," European Journal of Operational Research, Elsevier, vol. 305(1), pages 400-428.
    16. Caunhye, Aakil M. & Li, Mingzhe & Nie, Xiaofeng, 2015. "A location-allocation model for casualty response planning during catastrophic radiological incidents," Socio-Economic Planning Sciences, Elsevier, vol. 50(C), pages 32-44.
    17. Snoeck, André & Winkenbach, Matthias & Fransoo, Jan C., 2023. "On-demand last-mile distribution network design with omnichannel inventory," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 180(C).
    18. Snoeck, André & Winkenbach, Matthias & Fransoo, Jan C., 2023. "On-demand last-mile distribution network design with omnichannel inventory," Other publications TiSEM 83b06c9f-2a65-4aaf-880b-2, Tilburg University, School of Economics and Management.
    19. Deniz Preil & Michael Krapp, 2023. "Genetic multi-armed bandits: a reinforcement learning approach for discrete optimization via simulation," Papers 2302.07695, arXiv.org.
    20. Wang, Wei & Wu, Shining & Wang, Shuaian & Zhen, Lu & Qu, Xiaobo, 2021. "Emergency facility location problems in logistics: Status and perspectives," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).

    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:309:y:2023:i:3:p:1237-1262. 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.