IDEAS home Printed from https://ideas.repec.org/a/kap/hcarem/v20y2017i2d10.1007_s10729-015-9341-3.html
   My bibliography  Save this article

A dynamic ambulance management model for rural areas

Author

Listed:
  • T. C. Barneveld

    (Centrum Wiskunde & Informatica)

  • S. Bhulai

    (VU University Amsterdam)

  • R. D. Mei

    (Centrum Wiskunde & Informatica)

Abstract

We study the Dynamic Ambulance Management (DAM) problem in which one tries to retain the ability to respond to possible future requests quickly when ambulances become busy. To this end, we need models for relocation actions for idle ambulances that incorporate different performance measures related to response times. We focus on rural regions with a limited number of ambulances. We model the region of interest as an equidistant graph and we take into account the current status of both the system and the ambulances in a state. We do not require ambulances to return to a base station: they are allowed to idle at any node. This brings forth a high degree of complexity of the state space. Therefore, we present a heuristic approach to compute redeployment actions. We construct several scenarios that may occur one time-step later and combine these scenarios with each feasible action to obtain a classification of actions. We show that on most performance indicators, the heuristic policy significantly outperforms the classical compliance table policy often used in practice.

Suggested Citation

  • T. C. Barneveld & S. Bhulai & R. D. Mei, 2017. "A dynamic ambulance management model for rural areas," Health Care Management Science, Springer, vol. 20(2), pages 165-186, June.
  • Handle: RePEc:kap:hcarem:v:20:y:2017:i:2:d:10.1007_s10729-015-9341-3
    DOI: 10.1007/s10729-015-9341-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10729-015-9341-3
    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/s10729-015-9341-3?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. 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.
    2. Brotcorne, Luce & Laporte, Gilbert & Semet, Frederic, 2003. "Ambulance location and relocation models," European Journal of Operational Research, Elsevier, vol. 147(3), pages 451-463, June.
    3. Constantine Toregas & Ralph Swain & Charles ReVelle & Lawrence Bergman, 1971. "The Location of Emergency Service Facilities," Operations Research, INFORMS, vol. 19(6), pages 1363-1373, October.
    4. M Gendreau & G Laporte & F Semet, 2006. "The maximal expected coverage relocation problem for emergency vehicles," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(1), pages 22-28, January.
    5. Rajan Batta & June M. Dolan & Nirup N. Krishnamurthy, 1989. "The Maximal Expected Covering Location Problem: Revisited," Transportation Science, INFORMS, vol. 23(4), pages 277-287, November.
    6. Peter Kolesar & Warren E. Walker, 1974. "An Algorithm for the Dynamic Relocation of Fire Companies," Operations Research, INFORMS, vol. 22(2), pages 249-274, April.
    7. Matthew S. Maxwell & Mateo Restrepo & Shane G. Henderson & Huseyin Topaloglu, 2010. "Approximate Dynamic Programming for Ambulance Redeployment," INFORMS Journal on Computing, INFORMS, vol. 22(2), pages 266-281, May.
    8. Schmid, Verena, 2012. "Solving the dynamic ambulance relocation and dispatching problem using approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 219(3), pages 611-621.
    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. van Barneveld, Thije & Jagtenberg, Caroline & Bhulai, Sandjai & van der Mei, Rob, 2018. "Real-time ambulance relocation: Assessing real-time redeployment strategies for ambulance relocation," Socio-Economic Planning Sciences, Elsevier, vol. 62(C), pages 129-142.
    2. Bélanger, V. & Ruiz, A. & Soriano, P., 2019. "Recent optimization models and trends in location, relocation, and dispatching of emergency medical vehicles," European Journal of Operational Research, Elsevier, vol. 272(1), pages 1-23.
    3. Ľuboš Buzna & Peter Czimmermann, 2021. "On the Modelling of Emergency Ambulance Trips: The Case of the Žilina Region in Slovakia," Mathematics, MDPI, vol. 9(17), pages 1-30, September.
    4. Drent, Collin & Keizer, Minou Olde & Houtum, Geert-Jan van, 2020. "Dynamic dispatching and repositioning policies for fast-response service networks," European Journal of Operational Research, Elsevier, vol. 285(2), pages 583-598.
    5. 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.

    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. van Barneveld, Thije & Jagtenberg, Caroline & Bhulai, Sandjai & van der Mei, Rob, 2018. "Real-time ambulance relocation: Assessing real-time redeployment strategies for ambulance relocation," Socio-Economic Planning Sciences, Elsevier, vol. 62(C), pages 129-142.
    2. Martin van Buuren & Caroline Jagtenberg & Thije van Barneveld & Rob van der Mei & Sandjai Bhulai, 2018. "Ambulance Dispatch Center Pilots Proactive Relocation Policies to Enhance Effectiveness," Interfaces, INFORMS, vol. 48(3), pages 235-246, June.
    3. Boyacı, Burak & Geroliminis, Nikolas, 2015. "Approximation methods for large-scale spatial queueing systems," Transportation Research Part B: Methodological, Elsevier, vol. 74(C), pages 151-181.
    4. 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.
    5. McCormack, Richard & Coates, Graham, 2015. "A simulation model to enable the optimization of ambulance fleet allocation and base station location for increased patient survival," European Journal of Operational Research, Elsevier, vol. 247(1), pages 294-309.
    6. Bélanger, V. & Ruiz, A. & Soriano, P., 2019. "Recent optimization models and trends in location, relocation, and dispatching of emergency medical vehicles," European Journal of Operational Research, Elsevier, vol. 272(1), pages 1-23.
    7. Sudtachat, Kanchala & Mayorga, Maria E. & Mclay, Laura A., 2016. "A nested-compliance table policy for emergency medical service systems under relocation," Omega, Elsevier, vol. 58(C), pages 154-168.
    8. Thije van Barneveld, 2016. "The Minimum Expected Penalty Relocation Problem for the Computation of Compliance Tables for Ambulance Vehicles," INFORMS Journal on Computing, INFORMS, vol. 28(2), pages 370-384, May.
    9. Dmitrii Usanov & G.A. Guido Legemaate & Peter M. van de Ven & Rob D. van der Mei, 2019. "Fire truck relocation during major incidents," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(2), pages 105-122, March.
    10. Soovin Yoon & Laura A. Albert, 2018. "An expected coverage model with a cutoff priority queue," Health Care Management Science, Springer, vol. 21(4), pages 517-533, December.
    11. van Barneveld, T.C. & Bhulai, S. & van der Mei, R.D., 2016. "The effect of ambulance relocations on the performance of ambulance service providers," European Journal of Operational Research, Elsevier, vol. 252(1), pages 257-269.
    12. M Gendreau & G Laporte & F Semet, 2006. "The maximal expected coverage relocation problem for emergency vehicles," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(1), pages 22-28, January.
    13. Cheng, Yung-Hsiang & Liang, Zheng-Xian, 2014. "A strategic planning model for the railway system accident rescue problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 69(C), pages 75-96.
    14. Schmid, Verena, 2012. "Solving the dynamic ambulance relocation and dispatching problem using approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 219(3), pages 611-621.
    15. Bertsimas, Dimitris & Ng, Yeesian, 2019. "Robust and stochastic formulations for ambulance deployment and dispatch," European Journal of Operational Research, Elsevier, vol. 279(2), pages 557-571.
    16. Enayati, Shakiba & Mayorga, Maria E. & Rajagopalan, Hari K. & Saydam, Cem, 2018. "Real-time ambulance redeployment approach to improve service coverage with fair and restricted workload for EMS providers," Omega, Elsevier, vol. 79(C), pages 67-80.
    17. Kenneth C. Chong & Shane G. Henderson & Mark E. Lewis, 2016. "The Vehicle Mix Decision in Emergency Medical Service Systems," Manufacturing & Service Operations Management, INFORMS, vol. 18(3), pages 347-360, July.
    18. Phillip R. Jenkins & Matthew J. Robbins & Brian J. Lunday, 2021. "Approximate Dynamic Programming for Military Medical Evacuation Dispatching Policies," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 2-26, January.
    19. 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.
    20. Amir Ali Nasrollahzadeh & Amin Khademi & Maria E. Mayorga, 2018. "Real-Time Ambulance Dispatching and Relocation," Manufacturing & Service Operations Management, INFORMS, vol. 20(3), pages 467-480, July.

    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:kap:hcarem:v:20:y:2017:i:2:d:10.1007_s10729-015-9341-3. 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.