Research on Multi-Target Routing Problem of Coal Emergency Logistics Vehicles Based on Genetic Algorithm

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Authors

  • Peng Jiang
     School of Information Management, Jiangxi University of Finance & Economics, Nanchang 330 013 ,CN
  • Xiaohong Gan
     School of Information Management, Jiangxi University of Finance & Economics, Nanchang 330 013 ,CN

Keywords:

Coal Emergency Logistics Vehicles, Genetic Algorithm (GA), Routing Problem, Maximum Number of Iterations, Control Parameters.

Abstract

The existing studies on the routing problem of emergency logistics vehicles emphasize on qualitative analysis over quantitative research. To solve the problem, this paper combines qualitative and quantitative methods into a mathematical model of the routing problem, and adopts the genetic algorithm (GA) to enhance the transport efficiency and reduce the accident loss. Due to the lack of research on the maximum number of iterations, control parameters, etc., the rationality of the proposed iteration number and parameters was tested through a case simulation on Matlab R2011b. Through repeated tests, it is proved that the GA, the maximum number of iterations and the control parameters can find the optimal solution for the routing problem and achieve the desirable effect. In addition, the authors discussed the impacts of different crossover probabilities and mutation probabilities on the solution time and accuracy. This research provides strong supports to emergency management agencies in transport route design, allocation of relief items, manpower and vehicles, and reduction of disaster loss.

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Published

2022-10-22

How to Cite

Jiang, P., & Gan, X. (2022). Research on Multi-Target Routing Problem of Coal Emergency Logistics Vehicles Based on Genetic Algorithm. Journal of Mines, Metals and Fuels, 66(8), 405–413. Retrieved from http://informaticsjournals.com/index.php/jmmf/article/view/31728

Issue

Volume 66, Issue 8, August 2018

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

 

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