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- W4313549065 abstract "We introduce a multi-rule generation strategy into the conventional chaotic evolution (CE) to solve multimodal optimization, that is, a single run can find as many different optimal solutions as possible. To maintain the diversity of the population and avoid the over-density of individuals in the same local area, our proposal provides a variety of different rules to search the parameter space. Specifically, the proposed strategy will choose an appropriate rule for each individual to generate the offspring individual according to the distribution of individuals in its local area. To evaluate the effectiveness of our proposed strategy, we run the conventional CE and (the conventional CE + our proposed strategy) on 8 benchmark functions that have different characteristics and multiple levels of optimization difficulty. Besides, we also apply the Wilcoxon signed-rank test to detect significant differences between the two comparison algorithms at the stop condition. The experimental results confirmed that our proposed strategy can significantly find more different optimal solutions." @default.
- W4313549065 created "2023-01-06" @default.
- W4313549065 creator A5038291633 @default.
- W4313549065 creator A5072343551 @default.
- W4313549065 date "2022-11-29" @default.
- W4313549065 modified "2023-09-26" @default.
- W4313549065 title "Chaotic Evolution for Multimodal Optimization Based on Multi-rule Generation Strategy" @default.
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- W4313549065 doi "https://doi.org/10.1109/scisisis55246.2022.10002069" @default.
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