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Allocation of Resources for Emergency Response to Coal-to-Oil Hazardous Chemical Accidents under Railway Transportation Mode

Author

Listed:
  • Kaigong Zhao

    (School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China
    CHN Energy Shuohuang Railway Development Co., Suning Branch, Ltd., Cangzhou 062350, China)

  • Xiaolei Zhang

    (China Academy of Safety Science and Technology, Beijing 100012, China
    School of Emergency Management and Safety Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China)

  • Hui Wang

    (China Shenhua Energy Company Limited, Beijing 100011, China)

  • Yongling Gai

    (Jiuquan Satellite Launch Centre of China, Jiuquan 732750, China)

  • Haiyan Wang

    (School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China)

Abstract

Railways of the National Energy Group using their own trains have become an important mode of transportation for coal-to-oil hazardous chemicals. Under the circumstances of the shortage of emergency resources and the coupling of multiple disasters, how to establish an effective and reasonable emergency resource allocation scheme for the railway transportation of dangerous chemicals from a disaster site is of great significance to the national task of ensuring safety for the transportation of energy. This paper focuses on the allocation of emergency rescue resources for railway transportation accidents involving coal-to-oil hazardous chemicals, considering the scenarios of the leakage of coal-to-oil, railway line damage, etc. According to the number of trapped people at the initial moment, the disaster situation and accident type, affected areas, etc., a multi-objective optimization model with the shortest response time of the emergency team and the lowest cost of transporting emergency materials along the railway transportation channel of coal-to-oil hazardous chemicals is constructed, based on the calculation method using the initial weight and the emergency weight assigned by the emergency rescue team. Furthermore, in order to avoid the problem of the weight of the local accident points being too small to participate in a rescue, a bee colony algorithm model based on pre-allocation was designed and compared with two traditional algorithms, allowing the realization of the search and selection of allocation methods. The analysis of the examples shows that the proposed method is efficient and fast, and the research results are practical and feasible, which can provide a scientific basis for the rapid decision of emergency rescue resource allocation in multi-disaster scenarios for large energy groups, and provide a reference for the allocation of public security emergency resources in the national emergency response.

Suggested Citation

  • Kaigong Zhao & Xiaolei Zhang & Hui Wang & Yongling Gai & Haiyan Wang, 2022. "Allocation of Resources for Emergency Response to Coal-to-Oil Hazardous Chemical Accidents under Railway Transportation Mode," Sustainability, MDPI, vol. 14(24), pages 1-15, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16777-:d:1003289
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    References listed on IDEAS

    as
    1. Jianfeng Lu & Xiaoxia Wang & Jiahong Zhao, 2021. "Optimization of Emergency Supplies Scheduling for Hazardous Chemicals Storage Considering Risk," Sustainability, MDPI, vol. 13(19), pages 1-15, September.
    2. Yanyan Wang & Baiqing Sun, 2022. "Multiperiod optimal emergency material allocation considering road network damage and risk under uncertain conditions," Operational Research, Springer, vol. 22(3), pages 2173-2208, July.
    3. Ginger Y. Ke & Xun-Feng Hu & Xiao-Long Xue, 2022. "Using the Shapley Value to Mitigate the Emergency Rescue Risk for Hazardous Materials," Group Decision and Negotiation, Springer, vol. 31(1), pages 137-152, February.
    4. Ying Lu & Shuqi Sun, 2020. "Scenario-Based Allocation of Emergency Resources in Metro Emergencies: A Model Development and a Case Study of Nanjing Metro," Sustainability, MDPI, vol. 12(16), pages 1-21, August.
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