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.
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Acknowledgments
This research is partly supported by Humanity and Social Science Youth foundation of Ministry of Education of China (Grant No. 12YJCZH179), the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (Grant No. 16KJA110001), the National Natural Science Foundation of China (Grant No. 11371197), the Foundation of Jiangsu Key Laboratory for NSLSCS (Grant No. 201601). The authors thank the anonymous reviewers for providing valuable comments to improve this paper, and add special thanks to Professor Mohammed El-Abd and Cao zijian for providing the source codes of the comparative algorithms (GBSO, IRGBSO, BSODE).
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Sun, Y., Jin, Y., Wang, D. (2018). Brain Storm Optimization with Multi-population Based Ensemble of Creating Operations. In: Tan, Y., Shi, Y., Tang, Q. (eds) Advances in Swarm Intelligence. ICSI 2018. Lecture Notes in Computer Science(), vol 10941. Springer, Cham. https://doi.org/10.1007/978-3-319-93815-8_36
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DOI: https://doi.org/10.1007/978-3-319-93815-8_36
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