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A niching chaos optimization algorithm for multimodal optimization

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Abstract

Niching is the technique of finding and preserving multiple stable niches, or favorable parts of the solution space possibly around multiple optima, for the purpose of solving multimodal optimization problems. Chaos optimization algorithm (COA) is one of the global optimization techniques, but as far as we know, a niching variant of COA has not been developed . In this paper, a novel niching chaos optimization algorithm (NCOA) is proposed. The circle map with a proper parameter setting is employed considering the fact that the performance of COA is affected by the chaotic map. In order to achieve niching, NCOA utilizes several techniques including simultaneously contracted multiple search scopes, deterministic crowding and clearing. The effects of some components and parameters of NCOA are investigated through numerical experiments. Comparison with other state-of-the-art multimodal optimization algorithms demonstrates the competitiveness of the proposed NCOA.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 61375081) and the special fund project of Harbin science and technology innovation talents research (No. RC2013XK010002).

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Authors and Affiliations

  1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, People’s Republic of China

    Cholmin Rim, Songhao Piao & Guo Li

  2. Department of Electronics and Automation, Kim Il Sung University, Pyongyang, Democratic People’s Republic of Korea

    Cholmin Rim & Unsun Pak

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  1. Cholmin Rim
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  2. Songhao Piao
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  3. Guo Li
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  4. Unsun Pak
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Correspondence to Songhao Piao.

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Communicated by V. Loia.

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Rim, C., Piao, S., Li, G. et al. A niching chaos optimization algorithm for multimodal optimization. Soft Comput 22, 621–633 (2018). https://doi.org/10.1007/s00500-016-2360-2

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