抄録
Particle swarm optimization (PSO) is a popular optimization technique known for its simplicity and effectiveness. This paper introduces a variant that achieves a better balance between exploration and exploitation, named DiPSO. DiPSO incorporates a novel strategy based on trends in mean distance between individuals for local exploitation control. Experiments on 29 benchmark functions demonstrate that DiPSO consistently outperforms the state-of-the-art variant of PSO. Convergence analysis reveals that DiPSO achieves faster convergence and superior solutions. These results highlight the effectiveness of DiPSO in solving optimization problems.
本文言語 | 英語 |
---|---|
ページ(範囲) | 1722-1724 |
ページ数 | 3 |
ジャーナル | IEEJ Transactions on Electrical and Electronic Engineering |
巻 | 18 |
号 | 10 |
DOI | |
出版ステータス | 出版済み - 2023/10 |
ASJC Scopus 主題領域
- 電子工学および電気工学