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A Learnable Artificial Bee Colony Algorithm for Numerical Function Optimization
Qi XB(亓祥波); Zhu YL(朱云龙); Nan L(南琳); Ma LB(马连博)
Department信息服务与智能控制技术研究室
Conference Name20th International Conference on Industrial Engineering and Engineering Management
Conference DateAugust 16-19, 2013
Conference PlaceBaotou, China
Source PublicationProceedings of 20th International Conference on Industrial Engineering and Engineering Management
PublisherSpringer Verlag
Publication PlaceHeidelberg, Germany
2013
Pages349-360
Indexed ByEI
EI Accession number20142217758932
Contribution Rank1
ISBN978-3-642-40062-9
KeywordLearnable Artificial Bee Colony Artificial Bee Colony Particle Swarm Optimization
AbstractTo improve optimizing performance of artificial bee colony (ABC), a new algorithm called learnable artificial bee colony (LABC) is presented in this paper. The new algorithm employs some available knowledge from the two optimization phases to guide the next optimization process. Eight benchmark functions are used to validate its optimization effect. The experimental results show that LABC outperforms ABC and particle swarm optimization (PSO) on most benchmark functions. LABC provides a new reference for improving optimization performance of ABC.
Language英语
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/13823
Collection信息服务与智能控制技术研究室
Recommended Citation
GB/T 7714
Qi XB,Zhu YL,Nan L,et al. A Learnable Artificial Bee Colony Algorithm for Numerical Function Optimization[C]. Heidelberg, Germany:Springer Verlag,2013:349-360.
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