A Hybrid Parallel Algorithm With Multiple Improved Strategies - Intelligent Information Processing XI Access content directly
Conference Papers Year : 2022

A Hybrid Parallel Algorithm With Multiple Improved Strategies

Tingting Wang
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  • PersonId : 1275194
Jeng-Shyang Pan
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  • PersonId : 1275195
Pei-Cheng Song
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  • PersonId : 1275196
Shu-Chuan Chu
  • Function : Author
  • PersonId : 1275186

Abstract

This paper proposes a novel hybrid parallel algorithm with multiple improved strategies. The whole population is divided into three subpopulations and each sub-population executes butterfly optimization algorithm, grey wolf optimization algorithm, and marine predator algorithm respectively. Meanwhile, they share information through three different communication strategies. And in order to improve the performance of the algorithm, the text uses the cubic chaotic mapping mechanism in the initialization stage. At the same time, the idea of adaptive parameter strategy is also introduced, so that some hyperparameters are changed along with the iteration. The results show that the algorithm can provide very competitive results, and is superior to the best algorithm in the literature on most test functions.
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hal-04178751 , version 1 (08-08-2023)

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Tingting Wang, Jeng-Shyang Pan, Pei-Cheng Song, Shu-Chuan Chu. A Hybrid Parallel Algorithm With Multiple Improved Strategies. 12th International Conference on Intelligent Information Processing (IIP), May 2022, Qingdao, China. pp.228-242, ⟨10.1007/978-3-031-03948-5_19⟩. ⟨hal-04178751⟩
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