Journal
ADVANCES IN SWARM INTELLIGENCE, ICSI 2016, PT I
Volume 9712, Issue -, Pages 469-478Publisher
SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/978-3-319-41000-5_47
Keywords
Brain storm optimization; Brain storm optimization in objective space; Multimodal optimization; Swarm intelligence
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The aim of multimodal optimization is to locate multiple peaks/optima in a single run and to maintain these found optima until the end of a run. In this paper, brain storm optimization in objective space (BSO-OS) algorithm is utilized to solve multimodal optimization problems. Our goal is to measure the performance and effectiveness of BSO-OS algorithm. The experimental tests are conducted on eight benchmark functions. Based on the experimental results, the conclusions could be made that the BSO-OS algorithm performs good on solving multimodal optimization problems. To obtain good performances on multimodal optimization problems, an algorithm needs to balance its global search ability and solutions maintenance ability.
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