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Finding of urban rainstorm and waterlogging disasters based on microblogging data and the location-routing problem model of urban emergency logistics

Author

Listed:
  • Xianhua Wu

    (Shanghai Maritime University
    Nanjing University of Information Science and Technology
    Nanjing University of Information Science and Technology)

  • Yaru Cao

    (Nanjing University of Information Science and Technology)

  • Yang Xiao

    (Nanjing University of Information Science and Technology)

  • Ji Guo

    (Shanghai Maritime University
    Nanjing University of Information Science and Technology
    Nanjing University of Information Science and Technology)

Abstract

Due to the climate change and the rapid progress of urbanization, extreme weather disasters such as urban rainstorm and waterlogging are frequent. Therefore, how to find the waterlogging points in the presence of disasters and how to optimize the distribution of urban emergency logistics and reduce the negative impact of disasters have become a hot and difficult issue for government departments and scholars. First of all, the idea and method of using the big data of microblogging to obtain urban rainstorm and waterlogging disasters and public sentiment are put forward. In addition,this thesis constructed the location-routing problem model of urban emergency logistics in the situation of rainstorm and waterlogging disaster, and found out the dynamic emergency distribution path of Nanjing in the situation of waterlogging disaster by using NSGA-III algorithm. Research shows that the risk management of urban rainstorm and waterlogging disasters, together with social media data, is a feasible way to obtain on-site data of disasters and carry out risk assessment of disasters. At the same time, the emergency logistics location-positioning model and algorithm can provide a reference for similar disaster emergency logistics distribution network and the conclusion can provide empirical reference for cities to cope with rainstorm and waterlogging disasters.

Suggested Citation

  • Xianhua Wu & Yaru Cao & Yang Xiao & Ji Guo, 2020. "Finding of urban rainstorm and waterlogging disasters based on microblogging data and the location-routing problem model of urban emergency logistics," Annals of Operations Research, Springer, vol. 290(1), pages 865-896, July.
    • Handle: RePEc:spr:annopr:v:290:y:2020:i:1:d:10.1007_s10479-018-2904-1
    DOI: 10.1007/s10479-018-2904-1
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    1. Mete, Huseyin Onur & Zabinsky, Zelda B., 2010. "Stochastic optimization of medical supply location and distribution in disaster management," International Journal of Production Economics, Elsevier, vol. 126(1), pages 76-84, July.
    2. Nasrin Asgari & Mohsen Rajabi & Masoumeh Jamshidi & Maryam Khatami & Reza Zanjirani Farahani, 2017. "A memetic algorithm for a multi-objective obnoxious waste location-routing problem: a case study," Annals of Operations Research, Springer, vol. 250(2), pages 279-308, March.
    3. Boni Su & Hong Huang & Yuntao Li, 2016. "Integrated simulation method for waterlogging and traffic congestion under urban rainstorms," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(1), pages 23-40, March.
    4. Leon Cooper, 1972. "The Transportation-Location Problem," Operations Research, INFORMS, vol. 20(1), pages 94-108, February.
    5. Boni Su & Hong Huang & Yuntao Li, 2016. "Integrated simulation method for waterlogging and traffic congestion under urban rainstorms," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(1), pages 23-40, March.
    6. Jotshi, Arun & Gong, Qiang & Batta, Rajan, 2009. "Dispatching and routing of emergency vehicles in disaster mitigation using data fusion," Socio-Economic Planning Sciences, Elsevier, vol. 43(1), pages 1-24, March.
    7. P. Mohapatra & A. Nayak & S.K. Kumar & M.K. Tiwari, 2015. "Multi-objective process planning and scheduling using controlled elitist non-dominated sorting genetic algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 53(6), pages 1712-1735, March.
    8. Ahmadi, Morteza & Seifi, Abbas & Tootooni, Behnam, 2015. "A humanitarian logistics model for disaster relief operation considering network failure and standard relief time: A case study on San Francisco district," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 75(C), pages 145-163.
    9. Zhou, Yawen & Liu, Jing & Zhang, Yutong & Gan, Xiaohui, 2017. "A multi-objective evolutionary algorithm for multi-period dynamic emergency resource scheduling problems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 99(C), pages 77-95.
    10. Yen-Yi Feng & I-Chin Wu & Tzu-Li Chen, 2017. "Stochastic resource allocation in emergency departments with a multi-objective simulation optimization algorithm," Health Care Management Science, Springer, vol. 20(1), pages 55-75, March.
    11. Moshref-Javadi, Mohammad & Lee, Seokcheon, 2016. "The Latency Location-Routing Problem," European Journal of Operational Research, Elsevier, vol. 255(2), pages 604-619.
    12. Wang, Haijun & Du, Lijing & Ma, Shihua, 2014. "Multi-objective open location-routing model with split delivery for optimized relief distribution in post-earthquake," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 69(C), pages 160-179.
    13. Jian-Liang Deng & Shui-Long Shen & Ye-Shuang Xu, 2016. "Investigation into pluvial flooding hazards caused by heavy rain and protection measures in Shanghai, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(2), pages 1301-1320, September.
    14. Ting, Ching-Jung & Chen, Chia-Ho, 2013. "A multiple ant colony optimization algorithm for the capacitated location routing problem," International Journal of Production Economics, Elsevier, vol. 141(1), pages 34-44.
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