IDEAS home Printed from https://ideas.repec.org/a/spr/operea/v23y2023i2d10.1007_s12351-023-00780-y.html
   My bibliography  Save this article

Ambulance dispatching and operating room scheduling considering reusable resources in mass-casualty incidents

Author

Listed:
  • Shuwan Zhu

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of Education)

  • Wenjuan Fan

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of Education)

  • Xueping Li

    (University of Tennessee)

  • Shanlin Yang

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of Education)

Abstract

Mass casualty incidents (MCIs) impose heavy demands on emergency response capabilities. It is essential to schedule limited emergency resources (e.g., ambulances, operating rooms, medical personnel, etc.) efficiently in order to maximize lifesaving capabilities. Most previous studies only consider a single type of emergency resource, which may result in inefficient coordination or bottlenecks between various types of resources. This paper addresses the combined problem of ambulance dispatching and operating room scheduling during an MCI. Specifically, we consider the limited ambulances and emergency operating rooms as reusable resources, more accurately reflecting reality than previous research. A novel mixed integer programming model aims to maximize the number of patients who can undergo surgery before their critical surgery time. A hybrid algorithm combining the Tabu Search and an Adaptive Large Neighborhood Search with five new specific removal operators is proposed for solving large-scale instances. The model is solved by Gurobi, and the results are compared with the proposed TS-ALNS. On small-scale instances, TS-ALNS is comparable to Gurobi, while on large-scale instances, it outperforms other meta-heuristics, including the Tabu search algorithm, the adaptive large neighborhood search algorithm, the simulated annealing algorithm, and the variable neighborhood search algorithm. In addition, the utilization and effectiveness of the five proposed removal operators are analyzed.

Suggested Citation

  • Shuwan Zhu & Wenjuan Fan & Xueping Li & Shanlin Yang, 2023. "Ambulance dispatching and operating room scheduling considering reusable resources in mass-casualty incidents," Operational Research, Springer, vol. 23(2), pages 1-37, June.
  • Handle: RePEc:spr:operea:v:23:y:2023:i:2:d:10.1007_s12351-023-00780-y
    DOI: 10.1007/s12351-023-00780-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12351-023-00780-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s12351-023-00780-y?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. 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. Almehdawe, Eman & Jewkes, Beth & He, Qi-Ming, 2016. "Analysis and optimization of an ambulance offload delay and allocation problem," Omega, Elsevier, vol. 65(C), pages 148-158.
    3. Kamali, Behrooz & Bish, Douglas & Glick, Roger, 2017. "Optimal service order for mass-casualty incident response," European Journal of Operational Research, Elsevier, vol. 261(1), pages 355-367.
    4. Evin Uzun Jacobson & Nilay Tanık Argon & Serhan Ziya, 2012. "Priority Assignment in Emergency Response," Operations Research, INFORMS, vol. 60(4), pages 813-832, August.
    5. Potvin, Jean-Yves & Rousseau, Jean-Marc, 1993. "A parallel route building algorithm for the vehicle routing and scheduling problem with time windows," European Journal of Operational Research, Elsevier, vol. 66(3), pages 331-340, May.
    6. Lamiri, Mehdi & Xie, Xiaolan & Dolgui, Alexandre & Grimaud, Frederic, 2008. "A stochastic model for operating room planning with elective and emergency demand for surgery," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1026-1037, March.
    7. 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.
    8. Armann Ingolfsson & Susan Budge & Erhan Erkut, 2008. "Optimal ambulance location with random delays and travel times," Health Care Management Science, Springer, vol. 11(3), pages 262-274, September.
    9. Eun, Joonyup & Kim, Sang-Phil & Yih, Yuehwern & Tiwari, Vikram, 2019. "Scheduling elective surgery patients considering time-dependent health urgency: Modeling and solution approaches," Omega, Elsevier, vol. 86(C), pages 137-153.
    10. Wilson, Duncan T. & Hawe, Glenn I. & Coates, Graham & Crouch, Roger S., 2013. "A multi-objective combinatorial model of casualty processing in major incident response," European Journal of Operational Research, Elsevier, vol. 230(3), pages 643-655.
    11. Alex F. Mills & Nilay Tanık Argon & Serhan Ziya, 2013. "Resource-Based Patient Prioritization in Mass-Casualty Incidents," Manufacturing & Service Operations Management, INFORMS, vol. 15(3), pages 361-377, July.
    12. Wenming Cheng & Peng Guo & Zeqiang Zhang & Ming Zeng & Jian Liang, 2012. "Variable Neighborhood Search for Parallel Machines Scheduling Problem with Step Deteriorating Jobs," Mathematical Problems in Engineering, Hindawi, vol. 2012, pages 1-20, September.
    13. Kyung Sung Jung & Michael Pinedo & Chelliah Sriskandarajah & Vikram Tiwari, 2019. "Scheduling Elective Surgeries with Emergency Patients at Shared Operating Rooms," Production and Operations Management, Production and Operations Management Society, vol. 28(6), pages 1407-1430, June.
    14. Abbas Al-Refaie & Toly Chen & Mays Judeh, 2018. "Optimal operating room scheduling for normal and unexpected events in a smart hospital," Operational Research, Springer, vol. 18(3), pages 579-602, October.
    15. 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).
    16. Duma, Davide & Aringhieri, Roberto, 2019. "The management of non-elective patients: shared vs. dedicated policies," Omega, Elsevier, vol. 83(C), pages 199-212.
    17. Kyohong Shin & Taesik Lee, 2020. "Emergency medical service resource allocation in a mass casualty incident by integrating patient prioritization and hospital selection problems," IISE Transactions, Taylor & Francis Journals, vol. 52(10), pages 1141-1155, October.
    18. G Barbarosoǧlu & Y Arda, 2004. "A two-stage stochastic programming framework for transportation planning in disaster response," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(1), pages 43-53, January.
    19. Almehdawe, Eman & Jewkes, Beth & He, Qi-Ming, 2013. "A Markovian queueing model for ambulance offload delays," European Journal of Operational Research, Elsevier, vol. 226(3), pages 602-614.
    20. Vallada, Eva & Ruiz, Rubén, 2011. "A genetic algorithm for the unrelated parallel machine scheduling problem with sequence dependent setup times," European Journal of Operational Research, Elsevier, vol. 211(3), pages 612-622, June.
    21. Repoussis, Panagiotis P. & Paraskevopoulos, Dimitris C. & Vazacopoulos, Alkiviadis & Hupert, Nathaniel, 2016. "Optimizing emergency preparedness and resource utilization in mass-casualty incidents," European Journal of Operational Research, Elsevier, vol. 255(2), pages 531-544.
    22. Sung, Inkyung & Lee, Taesik, 2016. "Optimal allocation of emergency medical resources in a mass casualty incident: Patient prioritization by column generation," European Journal of Operational Research, Elsevier, vol. 252(2), pages 623-634.
    23. Leo, Gianmaria & Lodi, Andrea & Tubertini, Paolo & Di Martino, Mirko, 2016. "Emergency Department Management in Lazio, Italy," Omega, Elsevier, vol. 58(C), pages 128-138.
    24. Lei Lei & Michael Pinedo & Lian Qi & Shengbin Wang & Jian Yang, 2015. "Personnel scheduling and supplies provisioning in emergency relief operations," Annals of Operations Research, Springer, vol. 235(1), pages 487-515, December.
    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. Shuwan Zhu & Wenjuan Fan & Shanlin Yang & Panos M. Pardalos, 2023. "Scheduling operating rooms of multiple hospitals considering transportation and deterioration in mass-casualty incidents," Annals of Operations Research, Springer, vol. 321(1), pages 717-753, February.
    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. 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.
    4. Rezapour, Shabnam & Naderi, Nazanin & Morshedlou, Nazanin & Rezapourbehnagh, Shaghayegh, 2018. "Optimal deployment of emergency resources in sudden onset disasters," International Journal of Production Economics, Elsevier, vol. 204(C), pages 365-382.
    5. Lee, Hyun-Rok & Lee, Taesik, 2021. "Multi-agent reinforcement learning algorithm to solve a partially-observable multi-agent problem in disaster response," European Journal of Operational Research, Elsevier, vol. 291(1), pages 296-308.
    6. Repoussis, Panagiotis P. & Paraskevopoulos, Dimitris C. & Vazacopoulos, Alkiviadis & Hupert, Nathaniel, 2016. "Optimizing emergency preparedness and resource utilization in mass-casualty incidents," European Journal of Operational Research, Elsevier, vol. 255(2), pages 531-544.
    7. Sean Harris & David Claudio, 2022. "Current Trends in Operating Room Scheduling 2015 to 2020: a Literature Review," SN Operations Research Forum, Springer, vol. 3(1), pages 1-42, March.
    8. Kamyabniya, Afshin & Noormohammadzadeh, Zohre & Sauré, Antoine & Patrick, Jonathan, 2021. "A robust integrated logistics model for age-based multi-group platelets in disaster relief operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    9. Kamali, Behrooz & Bish, Douglas & Glick, Roger, 2017. "Optimal service order for mass-casualty incident response," European Journal of Operational Research, Elsevier, vol. 261(1), pages 355-367.
    10. 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.
    11. 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).
    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. Yu Wang & Yu Zhang & Minglong Zhou & Jiafu Tang, 2023. "Feature‐driven robust surgery scheduling," Production and Operations Management, Production and Operations Management Society, vol. 32(6), pages 1921-1938, June.
    14. Tippong, Danuphon & Petrovic, Sanja & Akbari, Vahid, 2022. "A review of applications of operational research in healthcare coordination in disaster management," European Journal of Operational Research, Elsevier, vol. 301(1), pages 1-17.
    15. Hyun-Rok Lee & Taesik Lee, 2018. "Markov decision process model for patient admission decision at an emergency department under a surge demand," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 98-122, June.
    16. Hui Li & Jin Peng & Shengguo Li & Chuang Su, 2017. "Dispatching medical supplies in emergency events via uncertain programming," Journal of Intelligent Manufacturing, Springer, vol. 28(3), pages 549-558, March.
    17. Sheikholeslami, Mahnaz & Zarrinpoor, Naeme, 2023. "Designing an integrated humanitarian logistics network for the preparedness and response phases under uncertainty," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    18. Acuna, Jorge A. & Zayas-Castro, José L. & Charkhgard, Hadi, 2020. "Ambulance allocation optimization model for the overcrowding problem in US emergency departments: A case study in Florida," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    19. Elmira Farrokhizadeh & Seyed Amin Seyfi-Shishavan & Sule Itir Satoglu, 2022. "Blood supply planning during natural disasters under uncertainty: a novel bi-objective model and an application for red crescent," Annals of Operations Research, Springer, vol. 319(1), pages 73-113, December.
    20. Zhang, Jian & Dridi, Mahjoub & El Moudni, Abdellah, 2020. "Column-generation-based heuristic approaches to stochastic surgery scheduling with downstream capacity constraints," International Journal of Production Economics, Elsevier, vol. 229(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:spr:operea:v:23:y:2023:i:2:d:10.1007_s12351-023-00780-y. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.