抄録
In 2019, a completely new algorithm, spherical evolution (SE), was proposed. The brand new search style in SE has been proved to have a strong search capability. In order to take advantage of SE, we propose a novel method called the ladder descent (LD) method to improve the SE' population update strategy and thereafter propose a ladder spherical evolution search (LSE) algorithm. With the number of iterations increasing, the range of parent individuals eligible to produce offspring gradually changes from the entire population to the current optimal individual, thereby enhancing the convergence ability of the algorithm. Experiment results on IEEE CEC2017 benchmark functions indicate the effectiveness of LSE.
本文言語 | 英語 |
---|---|
ページ(範囲) | 461-464 |
ページ数 | 4 |
ジャーナル | IEICE Transactions on Information and Systems |
巻 | E104D |
号 | 3 |
DOI | |
出版ステータス | 出版済み - 2021/03/01 |
ASJC Scopus 主題領域
- ソフトウェア
- ハードウェアとアーキテクチャ
- コンピュータ ビジョンおよびパターン認識
- 電子工学および電気工学
- 人工知能