Using Grey Wolf Hunting Mechanism to Improve Brain Storm Optimization

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - 2018 5th International Conference on Information Science and Control Engineering, ICISCE 2018
EditorsShaozi Li, Ying Dai, Yun Cheng
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages602-606
Number of pages5
ISBN (Electronic)9781538655009
DOIs
StatePublished - 2018/07/02
Event5th International Conference on Information Science and Control Engineering, ICISCE 2018 - Zhengzhou, Henan, China
Duration: 2018/07/202018/07/22

Publication series

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

Conference

Conference5th International Conference on Information Science and Control Engineering, ICISCE 2018
Country/TerritoryChina
CityZhengzhou, Henan
Period2018/07/202018/07/22

Keywords

  • Brain storm optimization algorithm
  • brainstorming process
  • grey wolf optimization
  • optimization

ASJC Scopus subject areas

  • Decision Sciences (miscellaneous)
  • Information Systems and Management
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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