Location optimization of urban fire stations: access and service coverage

Yao, J. , Zhang, X. and Murray, A. T. (2019) Location optimization of urban fire stations: access and service coverage. Computers, Environment and Urban Systems, 73, pp. 184-190. (doi:10.1016/j.compenvurbsys.2018.10.006)

Yao, J. , Zhang, X. and Murray, A. T. (2019) Location optimization of urban fire stations: access and service coverage. Computers, Environment and Urban Systems, 73, pp. 184-190. (doi:10.1016/j.compenvurbsys.2018.10.006)

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Abstract

Fire and rescue services are among the most critical public services provided by governments to protect people, property and the environment from fires and other emergencies. Efficient deployment of fire stations is essential to ensure timely response to calls for service. Given the geographic nature of such problems, spatial optimization approaches have long been employed in public facility location modeling along these lines. In particular, median and coverage approaches have been widely adopted to help achieve travel-cost and service-coverage goals, respectively. This paper proposes a bi-objective spatial optimization model that integrates coverage and median goals in the service of demand areas. Based on the properties of derived objective functions, we presented a constraint-based solution procedure to generate the Pareto frontier, enabling the identification of alternative fire station siting scenarios. The developed model is applied to an empirical study that seeks to identify the best fire station locations in Nanjing, China. The results demonstrate the value of spatial optimization in assisting fire station planning and rescue resource deployment, highlighting important policy implications.

Item Type:Articles
Additional Information:Funder's name: National Natural Science Foundation of China, Grant ID: 41201117.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Yao, Dr Jing
Authors: Yao, J., Zhang, X., and Murray, A. T.
College/School:College of Social Sciences > School of Social and Political Sciences > Urban Studies
Journal Name:Computers, Environment and Urban Systems
Publisher:Elsevier
ISSN:0198-9715
ISSN (Online):1873-7587
Published Online:29 October 2018
Copyright Holders:Copyright © 2018 Elsevier Ltd.
First Published:First published in Computers, Environment and Urban Systems 73: 184-190
Publisher Policy:Reproduced in accordance with the publisher copyright policy

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