IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2022i1p627-d1019697.html
   My bibliography  Save this article

Location Optimization of Urban Fire Stations Considering the Backup Coverage

Author

Listed:
  • Liufeng Tao

    (School of Computer Science, China University of Geosciences, Wuhan 430074, China
    State Key Laboratory of Geo-Information Engineering, Xi’an 710000, China)

  • Yuqiong Cui

    (National Engineering Research Center of Geographic Information System, China University of Geosciences, Wuhan 430074, China)

  • Yongyang Xu

    (School of Computer Science, China University of Geosciences, Wuhan 430074, China
    State Key Laboratory of Geo-Information Engineering, Xi’an 710000, China
    Guangdong Hong Kong Macau Joint Laboratory for Smart Cities, Shenzhen 518034, China)

  • Zhanlong Chen

    (School of Computer Science, China University of Geosciences, Wuhan 430074, China)

  • Han Guo

    (Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen 518034, China)

  • Bo Huang

    (Wuhan Zondy Cyber Science and Technology Co., Ltd., Wuhan 430073, China)

  • Zhong Xie

    (School of Computer Science, China University of Geosciences, Wuhan 430074, China)

Abstract

Urban fires threaten the economic stability and safety of urban residents. Therefore, the limited number of fire stations should cover as many places as possible. Moreover, places with high fire risk should be covered by more fire stations. To optimize the location of urban fire stations, we construct a multi-objective optimization model for fire station planning based on the backup coverage model. The improved value of environment and ecosystem (SAVEE) model is introduced to quantify the spatial heterogeneity of urban fires. The main city zone of Wuhan is used as the study area to validate the proposed method. The results show that, considering the existing fire stations (85 facilities), the proposed model achieves a significant 38.56% in high-risk areas that can be covered by more than one fire station. If the existing fire stations are not considered when building 95 fire stations, the proposed model can achieve coverage of 50.07% in high-risk areas by utilizing more than one fire station. As a result, the proposed backup coverage model would perform better if the protection of high-risk areas is improved with as few fire stations as possible to guarantee more places covered.

Suggested Citation

  • Liufeng Tao & Yuqiong Cui & Yongyang Xu & Zhanlong Chen & Han Guo & Bo Huang & Zhong Xie, 2022. "Location Optimization of Urban Fire Stations Considering the Backup Coverage," IJERPH, MDPI, vol. 20(1), pages 1-18, December.
  • Handle: RePEc:gam:jijerp:v:20:y:2022:i:1:p:627-:d:1019697
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/1/627/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/20/1/627/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Constantine Toregas & Ralph Swain & Charles ReVelle & Lawrence Bergman, 1971. "The Location of Emergency Service Facilities," Operations Research, INFORMS, vol. 19(6), pages 1363-1373, October.
    2. Nyimbili, Penjani Hopkins & Erden, Turan, 2020. "GIS-based fuzzy multi-criteria approach for optimal site selection of fire stations in Istanbul, Turkey," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lee, Chungmok & Han, Jinil, 2017. "Benders-and-Price approach for electric vehicle charging station location problem under probabilistic travel range," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 130-152.
    2. Roberto Aringhieri & Giuliana Carello & Daniela Morale, 2016. "Supporting decision making to improve the performance of an Italian Emergency Medical Service," Annals of Operations Research, Springer, vol. 236(1), pages 131-148, January.
    3. Karl Schneeberger & Karl Doerner & Andrea Kurz & Michael Schilde, 2016. "Ambulance location and relocation models in a crisis," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 24(1), pages 1-27, March.
    4. Eliş, Haluk & Tansel, Barbaros & Oğuz, Osman & Güney, Mesut & Kian, Ramez, 2021. "On guarding real terrains: The terrain guarding and the blocking path problems," Omega, Elsevier, vol. 102(C).
    5. Davood Shishebori & Lawrence Snyder & Mohammad Jabalameli, 2014. "A Reliable Budget-Constrained FL/ND Problem with Unreliable Facilities," Networks and Spatial Economics, Springer, vol. 14(3), pages 549-580, December.
    6. P. Daniel Wright & Matthew J. Liberatore & Robert L. Nydick, 2006. "A Survey of Operations Research Models and Applications in Homeland Security," Interfaces, INFORMS, vol. 36(6), pages 514-529, December.
    7. Hamid Mousavi & Soroush Avakh Darestani & Parham Azimi, 2021. "An artificial neural network based mathematical model for a stochastic health care facility location problem," Health Care Management Science, Springer, vol. 24(3), pages 499-514, September.
    8. Jiwon Baik & Alan T. Murray, 2022. "Locating a facility to simultaneously address access and coverage goals," Papers in Regional Science, Wiley Blackwell, vol. 101(5), pages 1199-1217, October.
    9. Chen, Liang & Chen, Sheng-Jie & Chen, Wei-Kun & Dai, Yu-Hong & Quan, Tao & Chen, Juan, 2023. "Efficient presolving methods for solving maximal covering and partial set covering location problems," European Journal of Operational Research, Elsevier, vol. 311(1), pages 73-87.
    10. Erhan Erkut & Armann Ingolfsson & Güneş Erdoğan, 2008. "Ambulance location for maximum survival," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(1), pages 42-58, February.
    11. Xin Feng & Alan T. Murray, 2018. "Allocation using a heterogeneous space Voronoi diagram," Journal of Geographical Systems, Springer, vol. 20(3), pages 207-226, July.
    12. Zhu Jianming, 2014. "Non-linear Integer Programming Model and Algorithms for Connected p-facility Location Problem," Journal of Systems Science and Information, De Gruyter, vol. 2(5), pages 451-460, October.
    13. Tomaz Dentinho & Vasco Silva, 2012. "Optimization of Location Services in the city of Huambo. Confirmation of the Theory of Central Places," ERSA conference papers ersa12p254, European Regional Science Association.
    14. Kuby, Michael & Lim, Seow, 2005. "The flow-refueling location problem for alternative-fuel vehicles," Socio-Economic Planning Sciences, Elsevier, vol. 39(2), pages 125-145, June.
    15. Martin van Buuren & Caroline Jagtenberg & Thije van Barneveld & Rob van der Mei & Sandjai Bhulai, 2018. "Ambulance Dispatch Center Pilots Proactive Relocation Policies to Enhance Effectiveness," Interfaces, INFORMS, vol. 48(3), pages 235-246, June.
    16. Nelas, José & Dias, Joana, 2020. "Optimal Emergency Vehicles Location: An approach considering the hierarchy and substitutability of resources," European Journal of Operational Research, Elsevier, vol. 287(2), pages 583-599.
    17. P R Harper & S Phillips & J E Gallagher, 2005. "Geographical simulation modelling for the regional planning of oral and maxillofacial surgery across London," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(2), pages 134-143, February.
    18. Ranon Jientrakul & Chumpol Yuangyai & Klongkwan Boonkul & Pakinai Chaicharoenwut & Suriyaphong Nilsang & Sittiporn Pimsakul, 2022. "Integrating Spatial Risk Factors with Social Media Data Analysis for an Ambulance Allocation Strategy: A Case Study in Bangkok," Sustainability, MDPI, vol. 14(16), pages 1-15, August.
    19. Su, Qiang & Luo, Qinyi & Huang, Samuel H., 2015. "Cost-effective analyses for emergency medical services deployment: A case study in Shanghai," International Journal of Production Economics, Elsevier, vol. 163(C), pages 112-123.
    20. S. A. MirHassani & R. Ebrazi, 2013. "A Flexible Reformulation of the Refueling Station Location Problem," Transportation Science, INFORMS, vol. 47(4), pages 617-628, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:20:y:2022:i:1:p:627-:d:1019697. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.