A global best artificial bee colony algorithm for global optimization

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

卷:236

Review

Gao, Weifeng¹  Liu, Sanyang¹  Huang, Lingling¹ 

[1] Xidian Univ, Dept Appl Math, Xian 710071, Peoples R China

关键词: Artificial bee colony algorithm;    Initial population;    Variant artificial bee colony algorithm;    Search strategy;   

DOI  :  10.1016/j.cam.2012.01.013

来源: Elsevier

【 摘 要 】

The artificial bee colony (ABC) algorithm is a relatively new optimization technique which has been shown to be competitive to other population-based algorithms. However, there is still an insufficiency in the ABC algorithm regarding its solution search equation, which is good at exploration but poor at exploitation. Inspired by differential evolution (DE), we propose a modified ABC algorithm (denoted as ABC/best), which is based on that each bee searches only around the best solution of the previous iteration in order to improve the exploitation. In addition, to enhance the global convergence, when producing the initial population and scout bees, both chaotic systems and opposition-based learning method are employed. Experiments are conducted on a set of 26 benchmark functions. The results demonstrate good performance of ABC/best in solving complex numerical optimization problems when compared with two ABC based algorithms. (C) 2012 Elsevier B.V. All rights reserved.

【 授权许可】

Free