A Negatively Correlation-Based Selection Strategy for Parameter Adaptation in SHADE

Yanting Liu, Houtian He, Zhe Wang, Zesheng Zhang, Zhe Xu, Shangce Gao

研究成果: 書籍の章/レポート/会議録会議への寄与査読

抄録

Negatively correlated search (NCS) is a population-based metaheuristic algorithm inspired by human behaviors in cooperation. One of the main processes of NCS is to evaluate the Bhattacharyya distance of two generations of population and employ a 'winner takes all' selection strategy to possess good exploitation ability. SHADE is an efficient variant of differential evolution algorithm which embedded a success-history based parameter adaptation strategy and demonstrates strong exploration capability. In this paper, a simple hybridization of NCS and SHADE is presented, which employs the negatively correlated method in the selection strategy of success parameters of SHADE. Due to the combination of advantages of both algorithms, the newly proposed NC-SHADE performs excellently on CEC'2017 benchmark function suit and has superiority in comparison with other related algorithms.

本文言語英語
ホスト出版物のタイトルProceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019
出版社Institute of Electrical and Electronics Engineers Inc.
ページ180-184
ページ数5
ISBN(電子版)9781728146522
DOI
出版ステータス出版済み - 2019/12
イベント12th International Symposium on Computational Intelligence and Design, ISCID 2019 - Hangzhou, 中国
継続期間: 2019/12/142019/12/15

出版物シリーズ

名前Proceedings - 2019 12th International Symposium on Computational Intelligence and Design, ISCID 2019
1

学会

学会12th International Symposium on Computational Intelligence and Design, ISCID 2019
国/地域中国
CityHangzhou
Period2019/12/142019/12/15

ASJC Scopus 主題領域

  • 人工知能
  • コンピュータ サイエンスの応用
  • ハードウェアとアーキテクチャ
  • 情報システムおよび情報管理
  • 制御と最適化

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