IDEAS home Printed from https://ideas.repec.org/h/spr/isochp/978-3-319-47766-4_9.html
   My bibliography  Save this book chapter

Optimal Ambulance Dispatching

In: Markov Decision Processes in Practice

Author

Listed:
  • C. J. Jagtenberg

    (CWI)

  • S. Bhulai

    (VU University Amsterdam)

  • R. D. Mei

    (CWI)

Abstract

This chapter considers the ambulance dispatch problem, in which one must decide which ambulance to send to an incident in real time. In practice as well as in literature, it is commonly believed that the closest idle ambulance is the best choice. This chapter describes alternatives to the classical closest idle ambulance rule. Our first method is based on a Markov decision problem (MDP), which constitutes the first known MDP model for ambulance dispatching. Moreover, in the broader field of dynamic ambulance management, this is the first MDP that captures more than just the number of idle vehicles, while remaining computationally tractable for reasonably-sized ambulance fleets. We analyze the policy obtained from this MDP, and transform it to a heuristic for ambulance dispatching that can handle the real-time situation more accurately than our MDP states can describe. We evaluate our policies by simulating a realistic emergency medical services region in the Netherlands. For this region, we show that our heuristic reduces the fraction of late arrivals by 13% compared to the “closest idle” benchmark policy. This result sheds new light on the popular belief that deviating from the closest idle dispatch policy cannot greatly improve the objective.

Suggested Citation

  • C. J. Jagtenberg & S. Bhulai & R. D. Mei, 2017. "Optimal Ambulance Dispatching," International Series in Operations Research & Management Science, in: Richard J. Boucherie & Nico M. van Dijk (ed.), Markov Decision Processes in Practice, chapter 0, pages 269-291, Springer.
    • Handle: RePEc:spr:isochp:978-3-319-47766-4_9
    DOI: 10.1007/978-3-319-47766-4_9
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rautenstrauss, Maximiliane & Martin, Layla & Minner, Stefan, 2023. "Ambulance dispatching during a pandemic: Tradeoffs of categorizing patients and allocating ambulances," European Journal of Operational Research, Elsevier, vol. 304(1), pages 239-254.
    2. 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.
    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. Yoon, Soovin & Albert, Laura A., 2021. "Dynamic dispatch policies for emergency response with multiple types of vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    5. Yoon, Soovin & Albert, Laura A., 2020. "A dynamic ambulance routing model with multiple response," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(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:isochp:978-3-319-47766-4_9. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.