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Location Optimization of Urban Emergency Medical Service Stations: A Hierarchical Multi-objective Model with a New Encoding Method of Genetic Algorithm Solution

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Web and Wireless Geographical Information Systems (W2GIS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12473))

Abstract

Since patients’ lives are closely bound up with emergency medical services, extensive studies to improve the quality of emergency services haves been receiving special attention. This paper presents a novel hierarchical multi-objective optimization model that considers the goal of providing effectiveness equal service for all citizens firstly, reducing the total travel cost of emergency medical service missions and the number of overall stations secondly, retaining as many existing stations as possible lastly to improve both the effectiveness equity and the efficiency of emergency medical service and reduce the financial cost. New methods of chromosome coding, crossover operation and mutation operation for preserving spatial configuration of regional variables in the process of genetic algorithm are developed and used to optimize locations of EMS stations in Shanghai, China. The results demonstrate that better planning of emergency medical service stations whose service area cover all area within 4 km can reduce travel costs by 70% with 13 new built up and 8 existing stations. Due to these promising results, the new encoded methods applied in this study are not only viable but also can be used in other urban areas to improve effectiveness equity of the emergency medical service.

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Acknowledgments

We are indebted to anonymous reviewers for insightful observations and suggestions that helped to improve our paper. This work is partially supported by the projects funded by the National Nature Science Foundation of China (grant numbers: 41771410 and 41401173).

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Authors and Affiliations

  1. Key Laboratory of Geographic Information Science (Ministry of Education) and School of Geographic Sciences, East China Normal University, Shanghai, China

    Jiajia Song, Xiang Li & Joseph Mango

  2. Department of Transportation and Geotechnical Engineering, University of Dar es Salaam, Dar es Salaam, Tanzania

    Joseph Mango

Authors
  1. Jiajia Song
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  2. Xiang Li
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  3. Joseph Mango
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Correspondence to Xiang Li .

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Editors and Affiliations

  1. University of Naples Federico II, Naples, Italy

    Sergio Di Martino

  2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China

    Zhixiang Fang

  3. Department of Computer Science and Engineering, Pusan National University, Pusan, Korea (Republic of)

    Ki-Joune Li

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Song, J., Li, X., Mango, J. (2020). Location Optimization of Urban Emergency Medical Service Stations: A Hierarchical Multi-objective Model with a New Encoding Method of Genetic Algorithm Solution. In: Di Martino, S., Fang, Z., Li, KJ. (eds) Web and Wireless Geographical Information Systems. W2GIS 2020. Lecture Notes in Computer Science(), vol 12473. Springer, Cham. https://doi.org/10.1007/978-3-030-60952-8_7

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  • DOI: https://doi.org/10.1007/978-3-030-60952-8_7

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-60952-8

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