Using Grey Wolf Hunting Mechanism to Improve Brain Storm Optimization

Shi Wang, Zonghui Cai, Yang Yu, Zhenyu Lei, 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

3 被引用数 (Scopus)

抄録

Brain storm optimization algorithm (BSO) is recently proposed population based optimization algorithm, which is inspired by the human brainstorming process. It is designed to solve global optimization problems and has a good performance in solving large-scale multidimensional multimodal problems. However, as it largely relies on the cluster center to update the population which makes it hard to exchange information within population, it can be frequently fall into the local optimal and can't get rid of this situation easily. Grey wolf optimization (GWO) algorithm has good abilities of global search and local area avoidance, thus, GWO is studied and combined with BSO to improve its ability of global search and avoid local optimal. The experiment results on CEC'17 benchmark function 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 5th International Conference on Information Science and Control Engineering, ICISCE 2018
編集者Shaozi Li, Ying Dai, Yun Cheng
出版社Institute of Electrical and Electronics Engineers Inc.
ページ602-606
ページ数5
ISBN(電子版)9781538655009
DOI
出版ステータス出版済み - 2018/07/02
イベント5th International Conference on Information Science and Control Engineering, ICISCE 2018 - Zhengzhou, Henan, 中国
継続期間: 2018/07/202018/07/22

出版物シリーズ

名前Proceedings - 2018 5th International Conference on Information Science and Control Engineering, ICISCE 2018

学会

学会5th International Conference on Information Science and Control Engineering, ICISCE 2018
国/地域中国
CityZhengzhou, Henan
Period2018/07/202018/07/22

ASJC Scopus 主題領域

  • 決定科学(その他)
  • 情報システムおよび情報管理
  • 制御およびシステム工学
  • 産業および生産工学

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