Particle Swarm Optimisation with Improved Learning Strategy
In this paper, a new variant of particle swarm optimisation (PSO) called PSO with improved learning strategy (PSO-ILS) is developed. Specifically, an ILS module is proposed to generate a more effective and efficient exemplar, which could offer a more promising search direction to the PSO-ILS part...
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| 主要な著者: | , |
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| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
Taylor's University
2015
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| 主題: | |
| オンライン･アクセス: | http://eprints.usm.my/42783/1/JES_Vol._11_2015_-_Art._4%2827-48%29.pdf http://eprints.usm.my/42783/ http://web.usm.my/jes/11_2015/JES%20Vol.%2011%202015%20-%20Art.%204(27-48).pdf |
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| 要約: | In this paper, a new variant of particle swarm optimisation (PSO) called PSO
with improved learning strategy (PSO-ILS) is developed. Specifically, an ILS module is
proposed to generate a more effective and efficient exemplar, which could offer a more
promising search direction to the PSO-ILS particle. Comparison is made on the PSO-ILS
with 6 well-established PSO variants on 10 benchmark functions to investigate the
optimisation capability of the proposed algorithm. The simulation results reveal that
PSO-ILS outperforms its peers for the majority of the tested benchmarks by
demonstrating superior search accuracy, reliability and efficiency. |
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