A Novel Backtracking Search with Grey Wolf Algorithm for Optimization

Dongbao Jia, Yining Tong, Yang Yu, Zonghui Cai, 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

6 被引用数 (Scopus)

抄録

Backtracking search optimization algorithm (BSA) is a new evolutionary algorithm. It is a population-based evolutionary algorithm designed to solve global optimization problems. It has a similar structure to differential evolution, including selection, mutation and crossover processes. This structure guarantees that BSA can utilize the information of the whole population and maintain the population diversity in a high level. While all these operations are randomly executed and have no directionality, which makes BSA can't direct the individuals to search the region that has been detected to be promising with better solutions. Thus, we combine BSA with grey wolf optimization to provide search motivation towards the better individuals. The experiment results on CEC'17 benchmark suit indicate the feasibility of this combination.

本文言語英語
ホスト出版物のタイトルProceedings - 2018 10th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2018
出版社Institute of Electrical and Electronics Engineers Inc.
ページ73-76
ページ数4
ISBN(電子版)9781538658369
DOI
出版ステータス出版済み - 2018/11/09
イベント10th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2018 - Hangzhou, 中国
継続期間: 2018/08/252018/08/26

出版物シリーズ

名前Proceedings - 2018 10th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2018
1

学会

学会10th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2018
国/地域中国
CityHangzhou
Period2018/08/252018/08/26

ASJC Scopus 主題領域

  • 人工知能
  • コンピュータ ビジョンおよびパターン認識
  • 人間とコンピュータの相互作用
  • 計算数学
  • 制御と最適化
  • コンピュータ サイエンスの応用

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