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2016 | OriginalPaper | Buchkapitel

An Improved Multi-strategy Ensemble Artificial Bee Colony Algorithm with Neighborhood Search

verfasst von : Xinyu Zhou, Mingwen Wang, Jianyi Wan, Jiali Zuo

Erschienen in: Neural Information Processing

Verlag: Springer International Publishing

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Abstract

Artificial bee colony (ABC) algorithm has been shown its good performance over many optimization problems. Recently, a multi-strategy ensemble ABC (MEABC) algorithm was proposed which employed three distinct solution search strategies. Although its such mechanism works well, it may run the risk of causing the problem of premature convergence when solving complex optimization problems. Hence, we present an improved version by integrating the neighborhood search operator of which object is to perturb the global best food source for better balancing the exploration and exploitation. Experiments are conducted on a set of 22 well-known benchmark functions, and the results show that both of the quality of final results and convergence speed can be improved.

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Metadaten
Titel
An Improved Multi-strategy Ensemble Artificial Bee Colony Algorithm with Neighborhood Search
verfasst von
Xinyu Zhou
Mingwen Wang
Jianyi Wan
Jiali Zuo
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-46681-1_58