Vehicle charging station location based on improved whale optimization algorithm

被引:0
|
作者
Li, Zhaodi [1 ]
Liu, Qingqing [2 ]
Yu, Kaixuan [3 ]
机构
[1] Henan Univ, Dept Comp & Informat Engn, Kaifeng, Peoples R China
[2] Henan Light Ind Vocat Coll, Dept Comp Sci & Art, Zhengzhou, Peoples R China
[3] State Key Lab Shield Machine & Boring Technol, Zhengzhou, Peoples R China
关键词
Whale optimization algorithm; Enhanced search; Location of charging station;
D O I
10.1109/ICCEA62105.2024.10603713
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In order to better explore a method for solving the problem of electric vehicle charging station location planning, and improve the shortcomings of whale algorithm such as weak stability, sometimes slow convergence speed and easy to fall into local extremum, a whale optimization algorithm with quasi-opposition-based learning and enhanced search mechanism was proposed. Then, the algorithm flow is given, and the CEC2017 test function set is simulated by six representative algorithms in multiple dimensions. The results show that the convergence speed, optimization accuracy and solution stability of the improved algorithm are significantly improved, and it has good convergence performance. In order to solve the problem of electric vehicle public charging station location and service area division, an improved whale algorithm and Voronoi diagram are used to jointly solve the location planning of charging station, so as to achieve the purpose of global optimization. The application results of the last example show that the improved whale algorithm can effectively solve the charging station location problem and has superior optimization performance.
引用
收藏
页码:1815 / 1819
页数:5
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