Accelerating Artificial Bee Colony Algorithm for Global Optimization
As an efficient optimization technique, artificial bee colony (ABC) algorithm has attracted a lot of attention for its good performance. However, ABC is good at exploration but poor at exploitation for its solution search equation. Thus, how to enhance the exploitation becomes an active research trend. In this paper, we propose a trigonometric search equation in which a hypergeometric triangle is formed to generate offspring. Additionally, the orthogonal learning strategy is integrated into the scout bee phase for generating new food source. Experiments are conducted on 23 well-known benchmark functions, and the results show that our approach has promising performance.
KeywordsArtificial bee colony Exploitative capability Trigonometric search equation Orthogonal learning
This work was supported by the Foundation of State Key Laboratory of Software Engineering (No. SKLSE2014-10-04), the National Natural Science Foundation of China (Nos. 61272212 and 61462045), the Science and Technology Foundation of Jiangxi Province (Nos. 20132BAB201030 and 20151BAB217007), and the Application Research Project of Nantong Science and Technology Bureau (No. BK2014057).
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