Location optimization of urban fire stations considering the variations in fire service demands: a bi-objective coverage model
Fire stations serve as operational hubs for firefighting and rescue teams, making their spatial optimization crucial to ensure effective urban firefighting and rescue operations. The traditional coverage model overlooks the difference in service satisfaction among various demand areas within the cov...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2025.2454386 |
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| _version_ | 1832585125209047040 |
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| author | Yulong Chen Jing Yao Shaohua Wang Zhizhu Lai Leying Wu Guanpeng Dong |
| author_facet | Yulong Chen Jing Yao Shaohua Wang Zhizhu Lai Leying Wu Guanpeng Dong |
| author_sort | Yulong Chen |
| collection | DOAJ |
| description | Fire stations serve as operational hubs for firefighting and rescue teams, making their spatial optimization crucial to ensure effective urban firefighting and rescue operations. The traditional coverage model overlooks the difference in service satisfaction among various demand areas within the coverage radius, making it less effective at optimizing fire station locations. This study examines the differing demands for fire services among various areas based on their levels of fire risk. We propose a bi-objective coverage (BOC) model to optimize the locations of urban fire stations by improving upon the traditional maximum coverage model and integrating it with the set coverage model. The [Formula: see text]-constraint method was applied to solve the constructed BOC model, obtaining the Pareto optimal frontier. Then, the BOC model was applied to address the spatial optimization of fire station locations in the central urban area of Zhengzhou City. Finally, a comparative analysis was performed on the optimization outcomes and performance of both the BOC and bi-objective spatial optimization (BSO) (integrating coverage and median goals) models. The computational results of the BOC model outperformed those of the BSO model in terms of both the effective service rate and the multiple coverage rate for demand areas. |
| format | Article |
| id | doaj-art-4e35516a2a5d49e58f859c9655537cdb |
| institution | Kabale University |
| issn | 1753-8947 1753-8955 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Digital Earth |
| spelling | doaj-art-4e35516a2a5d49e58f859c9655537cdb2025-01-27T02:44:20ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552025-12-0118110.1080/17538947.2025.2454386Location optimization of urban fire stations considering the variations in fire service demands: a bi-objective coverage modelYulong Chen0Jing Yao1Shaohua Wang2Zhizhu Lai3Leying Wu4Guanpeng Dong5Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization of Henan Province, Henan University, Kaifeng, People’s Republic of ChinaUrban Big Data Centre, School of Social and Political Sciences, University of Glasgow, Glasgow, UKKey Laboratory of Remote Sensing and Digital Earth Chinese Academy of Sciences, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaSchool of Geography and Environmental Engineering, Gannan Normal University, Ganzhou, People’s Republic of ChinaKey Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization of Henan Province, Henan University, Kaifeng, People’s Republic of ChinaKey Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization of Henan Province, Henan University, Kaifeng, People’s Republic of ChinaFire stations serve as operational hubs for firefighting and rescue teams, making their spatial optimization crucial to ensure effective urban firefighting and rescue operations. The traditional coverage model overlooks the difference in service satisfaction among various demand areas within the coverage radius, making it less effective at optimizing fire station locations. This study examines the differing demands for fire services among various areas based on their levels of fire risk. We propose a bi-objective coverage (BOC) model to optimize the locations of urban fire stations by improving upon the traditional maximum coverage model and integrating it with the set coverage model. The [Formula: see text]-constraint method was applied to solve the constructed BOC model, obtaining the Pareto optimal frontier. Then, the BOC model was applied to address the spatial optimization of fire station locations in the central urban area of Zhengzhou City. Finally, a comparative analysis was performed on the optimization outcomes and performance of both the BOC and bi-objective spatial optimization (BSO) (integrating coverage and median goals) models. The computational results of the BOC model outperformed those of the BSO model in terms of both the effective service rate and the multiple coverage rate for demand areas.https://www.tandfonline.com/doi/10.1080/17538947.2025.2454386Fire stationsservice satisfactionspatial optimizationcoverage modelbi-objective model |
| spellingShingle | Yulong Chen Jing Yao Shaohua Wang Zhizhu Lai Leying Wu Guanpeng Dong Location optimization of urban fire stations considering the variations in fire service demands: a bi-objective coverage model International Journal of Digital Earth Fire stations service satisfaction spatial optimization coverage model bi-objective model |
| title | Location optimization of urban fire stations considering the variations in fire service demands: a bi-objective coverage model |
| title_full | Location optimization of urban fire stations considering the variations in fire service demands: a bi-objective coverage model |
| title_fullStr | Location optimization of urban fire stations considering the variations in fire service demands: a bi-objective coverage model |
| title_full_unstemmed | Location optimization of urban fire stations considering the variations in fire service demands: a bi-objective coverage model |
| title_short | Location optimization of urban fire stations considering the variations in fire service demands: a bi-objective coverage model |
| title_sort | location optimization of urban fire stations considering the variations in fire service demands a bi objective coverage model |
| topic | Fire stations service satisfaction spatial optimization coverage model bi-objective model |
| url | https://www.tandfonline.com/doi/10.1080/17538947.2025.2454386 |
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