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Erschienen in:
2018 | OriginalPaper | Buchkapitel
Brain Storm Optimization with Multi-population Based Ensemble of Creating Operations
verfasst von : Yuehong Sun, Ye Jin, Dan Wang
Erschienen in: Advances in Swarm Intelligence
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Abstract
Brain storm optimization (BSO) algorithm is a novel swarm intelligence algorithm. Inspired by differential evolution (DE) with multi-population based ensemble of mutation strategies (MPEDE), a new variant of BSO algorithm, called brain storm optimization with multi-population based ensemble of creating operations (MPEBSO), is proposed in this paper. There are three equally sized smaller indicator subpopulations and one much larger reward subpopulation. BSO algorithm is used to update individuals in every subpopulation. At first, each creating operation has one smaller indicator subpopulation, in which different mutation strategy is used to add noise instead of the Gaussian random strategy. After every certain number of generations, the larger reward subpopulation will be adaptively assigned to the best performing creating operation with more computational resources. The competitive performance of the proposed MPEBSO on CEC2005 benchmark functions is highlighted compared with DE, MPEDE, and other four variants of BSO.