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Mathematical Problems in Engineering
Volume 2018, Article ID 3102628, 16 pages
https://doi.org/10.1155/2018/3102628
Research Article

An Improved Artificial Bee Colony Algorithm Based on Factor Library and Dynamic Search Balance

1School of Mechatronics Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China
2Institute of Electronic and Information Engineering of UESTC in Guangdong, Guangdong, China

Correspondence should be addressed to Wenjie Yu; moc.kooltuo@y.eijnew

Received 29 July 2017; Revised 12 December 2017; Accepted 20 December 2017; Published 28 January 2018

Academic Editor: Jose J. Muñoz

Copyright © 2018 Wenjie Yu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The artificial bee colony (ABC) algorithm is a relatively new optimization technique for simulating the honey bee swarms foraging behavior. Due to its simplicity and effectiveness, it has attracted much attention in recent years. However, ABC search equation is good at global search but poor at local search. Some different search equations are developed to tackle this problem, while there is no particular algorithm to substantially attain the best solution for all optimization problems. Therefore, we proposed an improved ABC with a new search equation, which incorporates the global search factor based on the optimization problem dimension and the local search factor based on the factor library (FL). Furthermore, aimed at preventing the algorithm from falling into local optima, dynamic search balance strategy is proposed and applied to replace the scout bee procedure in ABC. Thus, a hybrid, fast, and enhanced algorithm, HFEABC, is presented. In order to verify its effectiveness, some comprehensive tests among HFEABC and ABC and its variants are conducted on 21 basic benchmark functions and 20 complicated functions from CEC 2017. The experimental results show HFEABC offers better compatibility for different problems than ABC and some of its variants. The HFEABC performance is very competitive.