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Operations Research Applications in Health Care Management pp 395–421Cite as

OR Models for Emergency Medical Service (EMS) Management

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Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 262))

Abstract

Emergency Medical Service (EMS) systems provide pre-hospital medical assistance for those requiring prompt response and transportation. To realize such prompt response time at affordable cost, efficient planning of EMS is inevitable. Recently, these public safety systems have attracted considerable attention, since they provide remarkable services to people. Applying analytic techniques such as mathematical models and simulation models are becoming more common in emergency medical services. The intended mission of this chapter is to introduce and discuss the recent developments of Operations Research techniques for EMS management. Two selected mathematical models from the relevant literature are also elaborated. In addition, a real EMS location problem is described as a case study and finally a number of further research hints are presented.

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Author information

Authors and Affiliations

  1. School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

    S. M. Gholami-Zanjani & M. S. Pishvaee

  2. School of Industrial Engineering, University of Tehran, Tehran, Iran

    S. Ali Torabi

Authors
  1. S. M. Gholami-Zanjani
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  2. M. S. Pishvaee
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  3. S. Ali Torabi
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Corresponding author

Correspondence to S. Ali Torabi .

Editor information

Editors and Affiliations

  1. Department of Industrial Engineering, Istanbul Technical University, Macka, Istanbul, Turkey

    Cengiz Kahraman

  2. Department of Industrial Engineering, Istanbul Technical University, Macka, Istanbul, Turkey

    Y. Ilker Topcu

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Gholami-Zanjani, S.M., Pishvaee, M.S., Torabi, S.A. (2018). OR Models for Emergency Medical Service (EMS) Management. In: Kahraman, C., Topcu, Y. (eds) Operations Research Applications in Health Care Management. International Series in Operations Research & Management Science, vol 262. Springer, Cham. https://doi.org/10.1007/978-3-319-65455-3_16

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