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Emergency Rescue Vehicle Dispatch Planning Using a Hybrid Algorithm

Author

Listed:
  • Jie Cao

    (School of Public Administration and Collaborative Innovation, Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing Jiangsu 210044, P. R. China)

  • He Han

    (#x2020;School of Information & Control, Nanjing University of Information Science & Technology, Nanjing Jiangsu 210044, P. R. China)

  • Yi-Ping Jiang

    (#x2021;College of Engineering, Nanjing Agricultural University, Nanjing Jiangsu 210031, P. R. China)

  • Ya-Jing Wang

    (#xA7;Shuozhou Meteorological Bureau of Shanxi Province, Shanxi Shuozhou 038500, P. R. China)

Abstract

This paper describes the emergency rescue vehicle transportation network within the entire rescue period, and imitates rescue vehicle to select rescue route and to allocate emergency resource. The presented emergency rescue vehicle dispatch model seeks to minimize rescue time as the first objective function, minimize delay cost as the second objective function and maximize lifesaving utility as the last objective function in disaster response operations. To solve the proposed multiple objective model, a hybrid algorithm named nondominated sorting genetic algorithm (NSGA-II) with ant colony algorithm and a NSGA-II with random crossover and mutation, which can find better initial solution, are presented. In order to further prove the validity of the model and algorithm, a more complicated case is cited. Computational results are reported to illustrate the performance of the proposed model and algorithm. Statistical analysis confirms that the proposed random crossover and mutation operator outperforms the original crossover and mutation operator. The sensitivity analysis proves which parameter is more important for objective function values.

Suggested Citation

  • Jie Cao & He Han & Yi-Ping Jiang & Ya-Jing Wang, 2018. "Emergency Rescue Vehicle Dispatch Planning Using a Hybrid Algorithm," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(06), pages 1865-1890, November.
  • Handle: RePEc:wsi:ijitdm:v:17:y:2018:i:06:n:s0219622018500414
    DOI: 10.1142/S0219622018500414
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    References listed on IDEAS

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    Cited by:

    1. Ghazaleh Ahmadi & Reza Tavakkoli-Moghaddam & Armand Baboli & Mehdi Najafi, 2022. "A decision support model for robust allocation and routing of search and rescue resources after earthquake: a case study," Operational Research, Springer, vol. 22(2), pages 1039-1081, April.

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