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A Survey on Recent Optimization Strategies in Ambulance Dispatching and Relocation Problems

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Artificial Intelligence Doctoral Symposium (AID 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1852))

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Abstract

The COVID-19 pandemic disrupted and posed significant challenges to the healthcare transportation system. Since the pandemic spread around the world in February 2020, the Emergency Medical Services (EMS), which is the first healthcare provider at an emergency site and the system responsible for sending adequate care in a minimum amount of time, has been confronted with a massive number of emergency calls and a limited capacity of existing facilities (ambulances, hospitals). The challenge of EMS was to develop practical and effective methods for ensuring the quality of the service under various conditions in order to save people’s lives. The main focus of this study is to provide an overview and a discussion of modern modeling approaches designed in the literature to tackle problems with ambulance location and relocation as well as dispatching decisions. However, it reviews recent work on static and dynamic ambulance location problems. In this way, it is crucial to emphasize that the dynamic location of EMS is currently a relevant topic, given its influence on the outcomes of the healthcare system. Various significant contributions were proposed, including an analysis of summarized models, a presentation of recent approaches, and a recommendation for future advancements.

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Authors and Affiliations

  1. Laboratory for Research in Artificial Intelligence, USTHB, Algiers, Algeria

    Celia Khelfa & Ilyes Khennak

Authors
  1. Celia Khelfa
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  2. Ilyes Khennak
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Correspondence to Celia Khelfa .

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Editors and Affiliations

  1. University of Sciences and Technology Houari Boumediene, Algiers, Algeria

    Habiba Drias

  2. University of Technology of Troyes, Troyes, France

    Farouk Yalaoui

  3. Laboratory of Computer Science and Automatic Control for Systems, Poitiers, France

    Allel Hadjali

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Khelfa, C., Khennak, I. (2023). A Survey on Recent Optimization Strategies in Ambulance Dispatching and Relocation Problems. In: Drias, H., Yalaoui, F., Hadjali, A. (eds) Artificial Intelligence Doctoral Symposium. AID 2022. Communications in Computer and Information Science, vol 1852. Springer, Singapore. https://doi.org/10.1007/978-981-99-4484-2_15

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  • DOI: https://doi.org/10.1007/978-981-99-4484-2_15

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-4483-5

  • Online ISBN: 978-981-99-4484-2

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