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Artificial bee colony algorithm and pattern search hybridized for global optimization
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DOI：10.1016/j.asoc.2012.12.025.png)
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摘要
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Artificial bee colony algorithm is one of the most recently proposed swarm intelligence based optimization algorithm. A memetic algorithm which combines Hooke-Jeeves pattern search with artificial bee colony algorithm is proposed for numerical global optimization. There are two alternative phases of the proposed algorithm: the exploration phase realized by artificial bee colony algorithm and the exploitation phase completed by pattern search. The proposed algorithm was tested on a comprehensive set of benchmark functions, encompassing a wide range of dimensionality. Results show that the new algorithm is promising in terms of convergence speed, solution accuracy and success rate. The performance of artificial bee colony algorithm is much improved by introducing a pattern search method, especially in handling functions having narrow curving valley, functions with high eccentric ellipse and some complex multimodal functions. (C) 2013 Elsevier B. V. All rights reserved.
Keyword:
Artificial bee colony algorithm
Swarm intelligence
Memetic algorithm
Evolutionary computation
Global optimization
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6.6
论文数:
1.4W
被引数:
4.8W
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A hybrid genetic algorithm and particle swarm optimization for multimodal functions一种求解多峰函数的混合遗传粒子群算法
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