Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (13): 243-253.DOI: 10.3778/j.issn.1002-8331.1904-0159

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Vehicle Multiplication Solution Based on Random Forest and Variable Neighborhood Decline

GUO Yuhan, HU Dejia   

  1. College of Software, Liaoning Technical University, Huludao, Liaoning 125105, China
  • Online:2020-07-01 Published:2020-07-02



  1. 辽宁工程技术大学 软件学院,辽宁 葫芦岛 125105


In order to maximize users’ satisfaction, the Long-Term Car Pooling Problem(LTCPP) is modeled as a multi-objective optimization problem. Then, according to historical carpooling data and user satisfaction information, random forest algorithm is used to calculate the importance of each feature on users’ satisfaction, and it is used as the weight of the corresponding optimization objective, so as to avoid the influence of artificial setting weight factor on the optimization results. Finally, a Variable Neighborhood Descent(VND) algorithm for LTCPP is proposed, and the optimal solution of the problem is obtained by sequentially searching in multiple neighborhoods. The experimental results show that the VND algorithm can provide a high quality solution for LTCPP, and has a high time efficiency.

Key words: carpooling problem, multi-objective optimization, random forest, Variable Neighborhood Descent(VND)



关键词: 车辆合乘, 多目标优化, 随机森林, 变邻域下降