A Two-layer Encoding Learning Swarm Optimizer based on Frequent Itemsets for Sparse Large-scale Multi-objective Optimization

doi:10.1109/JAS.2024.124341

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	A Two-layer Encoding Learning Swarm Optimizer based on Frequent Itemsets for Sparse Large-scale Multi-objective Optimization
	Sheng Qi; Rui Wang; Tao Zhang; Xu Yang; Ruiqing Sun; Ling Wang
发表期刊	IEEE/CAA Journal of Automatica Sinica
ISSN	2329-9266
	2024
卷号	11 期号:6 页码:1342-1357
摘要	Traditional large-scale multi-objective optimization algorithms (LSMOEAs) encounter difficulties when dealing with sparse large-scale multi-objective optimization problems (SLMOPs) where most decision variables are zero. As a result, many algorithms use a two-layer encoding approach to optimize binary variable Mask and real variable Dec separately. Nevertheless, existing optimizers often focus on locating non-zero variable positions to optimize the binary variables Mask. However, approximating the sparse distribution of real Pareto optimal solutions does not necessarily mean that the objective function is optimized. In data mining, it is common to mine frequent itemsets appearing together in a dataset to reveal the correlation between data. Inspired by this, we propose a novel two-layer encoding learning swarm optimizer based on frequent itemsets (TELSO) to address these SLMOPs. TELSO mined the frequent terms of multiple particles with better target values to find mask combinations that can obtain better objective values for fast convergence. Experimental results on five real-world problems and eight benchmark sets demonstrate that TELSO outperforms existing state-of-the-art sparse large-scale multi-objective evolutionary algorithms (SLMOEAs) in terms of performance and convergence speed.
关键词	Evolutionary algorithms learning swarm optimization sparse large-scale optimization sparse large-scale multi-objective problems two-layer encoding
DOI	10.1109/JAS.2024.124341
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/56453
专题	学术期刊_IEEE/CAA Journal of Automatica Sinica
推荐引用方式 GB/T 7714	Sheng Qi,Rui Wang,Tao Zhang,et al. A Two-layer Encoding Learning Swarm Optimizer based on Frequent Itemsets for Sparse Large-scale Multi-objective Optimization[J]. IEEE/CAA Journal of Automatica Sinica,2024,11(6):1342-1357.
APA	Sheng Qi,Rui Wang,Tao Zhang,Xu Yang,Ruiqing Sun,&Ling Wang.(2024).A Two-layer Encoding Learning Swarm Optimizer based on Frequent Itemsets for Sparse Large-scale Multi-objective Optimization.IEEE/CAA Journal of Automatica Sinica,11(6),1342-1357.
MLA	Sheng Qi,et al."A Two-layer Encoding Learning Swarm Optimizer based on Frequent Itemsets for Sparse Large-scale Multi-objective Optimization".IEEE/CAA Journal of Automatica Sinica 11.6(2024):1342-1357.

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