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A Modified Particle Swarm Optimization Algorithm for Solving Capacitated Maximal Covering Location Problem in Healthcare Systems

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Applications of Intelligent Optimization in Biology and Medicine

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 96))

Abstract

Location-allocation decision of special facilities in healthcare is an emergent topic that is gaining noticeable attention especially in developing countries. Given the high cost of such facilities and the need to cover as much demand as possible, systematic methods are needed to be used to handle such a problem. In this chapter, a Capacitated Maximal Covering Location Problem (CMCLP) is used in order to model this problem. A proposed modified Particle Swarm Optimization (PSO) algorithm is used to solve the CMCLP. The solutions of the modified PSO algorithm is compared to GAMS outcomes, showing much better results. The proposed algorithm denotes promised results in pinpointing good locations for the facility maximizing the covered demand.

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Author information

Authors and Affiliations

  1. Department of Operations Research and Decision Support, Cairo University, Cairo, Egypt

    Sahar K. ElKady & Hisham M. Abdelsalam

Authors
  1. Sahar K. ElKady
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  2. Hisham M. Abdelsalam
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Correspondence to Hisham M. Abdelsalam .

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Editors and Affiliations

  1. Information Technology Department, Cairo University, Giza, Egypt

    Aboul-Ella Hassanien

  2. Department of Information Systems and Computing, Brunel University, London, United Kingdom

    Crina Grosan

  3. Faculty of Computers and information, Ain Shams University, Cairo, Egypt

    Mohamed Fahmy Tolba

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ElKady, S.K., Abdelsalam, H.M. (2016). A Modified Particle Swarm Optimization Algorithm for Solving Capacitated Maximal Covering Location Problem in Healthcare Systems. In: Hassanien, AE., Grosan, C., Fahmy Tolba, M. (eds) Applications of Intelligent Optimization in Biology and Medicine. Intelligent Systems Reference Library, vol 96. Springer, Cham. https://doi.org/10.1007/978-3-319-21212-8_5

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  • DOI: https://doi.org/10.1007/978-3-319-21212-8_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21211-1

  • Online ISBN: 978-3-319-21212-8

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