A mind evolutionary artificial bee colony algorithm

被引：0
作者：
Bao, Li [1 ]
机构：
[1] Department of Production, Communication University of Shanxi, Taiyuan, 030013, Shanxi
来源：
Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2015年 / 43卷 / 05期
关键词：
Artificial bee colony; Convergence; Global optimization; Mind evolutionary algorithm;
D O I：
10.3969/j.issn.0372-2112.2015.05.018
中图分类号：
学科分类号：
摘要：
Artificial bee colony (ABC) algorithm is a new global stochastic optimization algorithm, which mimics the intelligent behavior of honeybee swarms. It has been used to solve various optimization problems successfully. In order to further improve the performance of artificial bee colony algorithm, a mind evolutionary artificial bee colony algorithm (MEABC) based on the idea of mind evolutionary is proposed. Two strategies based on opposition learning and dimension up dating are applied to MEABC algorithm, and the convergence of the MEABC algorithm is analyzed. Experimental results on four benchmark functions show that the ME ABC algorithm can effectively avoid the premature convergence, greatly enhance t he global optimization ability and improve the convergence speed. ©, 2015, Chinese Institute of Electronics. All right reserved.
引用
收藏
页码：948 / 955
页数：7
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