Self Adaptive Artificial Bee Colony for Global Numerical Optimization

作     者：Wenxiang Gu Minghao Yin Chunying Wang 

作者机构：College of Computer Science Northeast Normal University Changchun 130117 P.R. China Changchun Architecture & Civil Engineering College Department of Basic Subject Teaching 130607 P.R. China 

出 版 物：《IERI Procedia》 

年 卷 期：2012年第1卷

页      面：59-65页

主　　题：artificial bee colony self adaptive global numerical optimization exploitation 

摘      要：The ABC algorithm has been used in many practical cases and has demonstrated good convergence rate. It produces the new solution according to the stochastic variance process. In this process, the magnitudes of the perturbation are important since it can affect the new solution. In this paper, we propose a self adaptive artificial bee colony, called self adaptive ABC, for the global numerical optimization. A new self adaptive perturbation is introduced in the basic ABC algorithm, in order to improve the convergence rates. 23 benchmark functions are employed in verifying the performance of self adaptive ABC. Experimental results indicate our approach is effective and efficient. Compared with other algorithms, self adaptive ABC performs better than, or at least comparable to the basic ABC algorithm and other state-of-the-art approaches from literature when considering the quality of the solution obtained.