Ambulances Deployment Problems: Categorization, Evolution and Dynamic Problems Review

Dionicio Neira-Rodado, John Wilmer Escobar-Velasquez, Sally I McClean

Research output: Contribution to journalReview articlepeer-review

8 Citations (Scopus)
140 Downloads (Pure)


In this paper, an analytic review of the recent methodologies tackling the problem of dynamic allocation of ambulances was carried out. Considering that state-of-the-art is moving to deal with more extensive and dynamic problems to address in a better way real-life instances, this research looks to identify the evolution and recent applications of this kind of problem once the basic models are explored. This extensive review allowed us to identify the most recent developments in this problem and the most critical gaps to be addressed. In this sense, it is essential to point out that the dynamic location of emergency medical services (EMS) is nowadays a relevant topic considering its impact on the healthcare system outcomes. Issues related to forecasting, simulation, heterogeneous fleets, robustness, and solution speed for real-life problems, stand out in the identified gaps. Applications of machine learning the deployment challenges during epidemic outbreaks such as SARS and COVID-19 were also explored. At the same time, a proposed notation tries to tackle the fact that the word problem in this kind of work refers to a model on many occasions. The proposed notation eases the comparison between the different model proposals found in the literature.

Original languageEnglish
Article number109
Pages (from-to)1-37
Number of pages37
JournalISPRS International Journal of Geo-Information
Issue number2
Publication statusPublished (in print/issue) - 3 Feb 2022

Bibliographical note

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.


  • Ambulance
  • Dispatch
  • Emergency
  • Emergency medical services (EMS)
  • Location
  • Optimization
  • Relocation
  • Routing


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