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Path-Relinking for Fire Station Location

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Intelligent Computing & Optimization (ICO 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 866))

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Abstract

In this paper, we propose the path relinking to solve the maximal covering location problem in which the demand points correspond to number of employees in industrial factories in Rayong, a province on the east coast of the Gulf of Thailand. According to the statistics for the fire in Thailand from 2012–2016; fire events tended upwards continuously from 2012 at 58.15 percent. Studying data on the fire to factories over the country in 2014–2015, Rayong province was high ranked fire occurrences which result in massive destruction. Path relinking algorithms are compared on the real-life instances to illustrate the efficiency of the proposed method.

Please note that the AISC Editorial assumes that all authors have used the western naming convention, with given names preceding surnames. This determines the structure of the names in the running heads and the author index.

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Acknowledgements

This research was funded by King Mongkut’s University of Technology North Bangkok. Contract No. KMUTNB-61-GOV-01-64.

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Authors and Affiliations

  1. King Mongkut’s University of Technology North Bangkok, 129 Moo 21 Neonhom, Mueng, Prachinburi, Thailand

    Titima Srianan & Ornurai Sangsawang

Authors
  1. Titima Srianan
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  2. Ornurai Sangsawang
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Corresponding author

Correspondence to Ornurai Sangsawang .

Editor information

Editors and Affiliations

  1. Department of Fundamental and Applied Sciences, Universiti Teknologi Petronas, Tronoh, Perak, Malaysia

    Pandian Vasant

  2. Faculty of Electrical Engineering and Computer Science, VŠB TU Ostrava, Ostrava, Czech Republic

    Ivan Zelinka

  3. Institute of Applied Mathematics, METU, Ankara, Ankara, Turkey

    Gerhard-Wilhelm Weber

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Srianan, T., Sangsawang, O. (2019). Path-Relinking for Fire Station Location. In: Vasant, P., Zelinka, I., Weber, GW. (eds) Intelligent Computing & Optimization. ICO 2018. Advances in Intelligent Systems and Computing, vol 866. Springer, Cham. https://doi.org/10.1007/978-3-030-00979-3_56

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  • DOI: https://doi.org/10.1007/978-3-030-00979-3_56

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00978-6

  • Online ISBN: 978-3-030-00979-3

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