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题名: A novel hybrid artificial bee colony algorithm with crossover operator for numerical optimization
作者: Yan XH(晏晓辉); Zhu YL(朱云龙); Chen HN(陈瀚宁); Zhang H(张浩)
作者部门: 信息服务与智能控制研究室
关键词: Artificial Bee Colony ; Hybrid artificial bee colony ; Crossover operator ; Crossover rate
刊名: Natural Computing
ISSN号: 1567-7818
出版日期: 2015
卷号: 14, 期号:1, 页码:169-184
收录类别: SCI ; EI
产权排序: 2
摘要: Artificial Bee Colony (ABC) algorithm is one of the most recently introduced swarm intelligence algorithms which inspired by the foraging behavior of honey bee swarms. It has been widely used in numerical and engineering optimization problems. This paper presents a hybrid artificial bee colony (HABC) model to improve the canonical ABC algorithm. The main idea of HABC is to enhance the information exchange between bees by introducing the crossover operator of genetic algorithm to ABC. With suitable crossover operation, valuable information is fully utilized and it is expected that the algorithm can converge faster and more accurate. Eight versions of HABC algorithm combined by different selection and crossover methods under the model were proposed and tested on several benchmark functions. Then, the settings of the new parameter crossover rate for two well performed HABC versions are tested to verify their best values. Finally, four rotated functions and four shifted functions are used to test the performance of the two algorithms on complex functions and asymmetric functions. Experiment results showed that these two versions of HABC algorithm offer significant improvement over the original ABC and are superior to other two state of the art algorithms on some functions. 漏 2013 Springer Science+Business Media Dordrecht.
语种: 英语
WOS记录号: WOS:000360155600013
WOS标题词: Science & Technology ; Technology
类目[WOS]: Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications ; Computer Science, Theory & Methods
关键词[WOS]: PARTICLE SWARM OPTIMIZATION ; GENETIC ALGORITHM ; DIFFERENTIAL EVOLUTION ; GLOBAL OPTIMIZATION ; PERFORMANCE
研究领域[WOS]: Computer Science
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内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/14682
Appears in Collections:信息服务与智能控制技术研究室_期刊论文

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