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题名: Discrete and Continuous Optimization Based on Hierarchical Artificial Bee Colony Optimizer
作者: Ma LB(马连博) ; Hu KY(胡琨元) ; Zhu YL(朱云龙) ; Niu B(牛奔) ; Chen HN(陈瀚宁) ; He MW(何茂伟)
作者部门: 信息服务与智能控制技术研究室
关键词: PARTICLE SWARM OPTIMIZER ; ABC ALGORITHM ; EVOLUTION
刊名: JOURNAL OF APPLIED MATHEMATICS
ISSN号: 1110-757X
出版日期: 2014
卷号: 2014, 页码:1-20
收录类别: SCI
产权排序: 1
摘要: This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization (HABC), to tackle complex high-dimensional problems. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operator is applied to enhance the global search ability between species. Experiments are conducted on a set of 20 continuous and discrete benchmark problems. The experimental results demonstrate remarkable performance of the HABC algorithm when compared with other six evolutionary algorithms.
WOS记录号: WOS:000333632600001
WOS标题词: Science & Technology ; Physical Sciences
类目[WOS]: Mathematics, Applied
关键词[WOS]: PARTICLE SWARM OPTIMIZER ; ABC ALGORITHM ; EVOLUTION
研究领域[WOS]: Mathematics
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内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/14743
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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