Search strategies investigation in brain storm optimization |
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| Authors: | Jingyu Wang Junfeng Chen Xingsi Xue Jingjing Du |
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| Institution: | 1.College of IOT Engineering,Hohai University,Changzhou,China;2.Jiangsu Key Laboratory of Power Transmission and Distribution Equipment,Hohai University,Changzhou,China;3.Changzhou Key Laboratory of Sensor Networks and Environmental Sensing,Changzhou,China;4.College of Information Science and Engineering,Fujian University of Technology,Fuzhou,China |
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| Abstract: | The canonical brain storm optimization (BSO) employs clustering, creating and selecting operators, which are all connected and have great impacts on the optimization performance. In this paper, the state-of-the-art search strategies are introduced and the potential strengths and weaknesses of these strategies in the BSO algorithm are analyzed and compared from the perspective of the analytical model rather than any metaphors. The numerical experiments are carried out to artificially amplify and highlight the performance of various strategies. Finally, the progressive directions of the BSO algorithm are discussed for further research. |
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