Neighborhood search-based artificial bee colony algorithm

被引:6
|
作者
Zhou, Xinyu [1 ,2 ]
Wu, Zhijian [1 ]
Deng, Changshou [3 ]
Peng, Hu [1 ]
机构
[1] State Key Laboratory of Software Engineering, Computer School, Wuhan University, Wuhan,430072, China
[2] College of Computer and Information Engineering, Jiangxi Normal University, Nanchang,330022, China
[3] School of Information Science & Technology, Jiujiang University, Jiujiang,332005, China
关键词
Evolutionary algorithms - Benchmarking;
D O I
10.11817/j.issn.1672-7207.2015.02.023
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The neighborhood search mechanism was introduced to improve the solution search equation of artificial bee colony algorithm. In the ring neighborhood topology of current food source, the exploitation was focused on the best neighbor food source to balance the capabilities of exploration and exploitation. Moreover, in order to preserve search experience for scout bees, the generalized opposition-based learning strategy was utilized to generate opposite solutions of the discarded food sources, which helps enhance the search efficiency. Twenty classic benchmark functions were used to test the performance of our approach, and then the experimental results were compared with other six well-known algorithms. The results show that our approach has better convergence speed and solution accuracy. ©, 2015, Central South University of Technology. All right reserved.
引用
收藏
页码:534 / 546
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