Gravitational Search Algorithm with Hierarchical Structure Guided by Elite Individual

Haotian Li, Yifei Yang, Haichuan Yang, Zheng Tang, Shangce Gao*

*Corresponding author for this work

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

7 Scopus citations

Abstract

The Gravitational Search Algorithm (GSA) is a Newtonian gravity-based meta-heuristic algorithm. The algorithm updates population members' locations according to the gravitational pull between them in order to solve the optimization issue. However, in some cases, the convergence of the algorithm is not fast enough. In order to improve the convergence speed of the algorithm while alleviating the problem of easily falling into local optima, we propose a gravitational search algorithm with hierarchical structure (EHGSA) guided by elite individuals. This structure can help the algorithm to have the ability to jump out of the local optimum while improving the convergence speed. The effectiveness of the proposed algorithm EHGSA is validated using the IEEE CEC2017 benchmark function test set of 29 functions.

Original languageEnglish
Title of host publicationProceedings - 2022 15th International Symposium on Computational Intelligence and Design, ISCID 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages180-184
Number of pages5
ISBN (Electronic)9781665456166
DOIs
StatePublished - 2022
Event15th International Symposium on Computational Intelligence and Design, ISCID 2022 - Hangzhou, China
Duration: 2022/12/172022/12/18

Publication series

NameProceedings - 2022 15th International Symposium on Computational Intelligence and Design, ISCID 2022

Conference

Conference15th International Symposium on Computational Intelligence and Design, ISCID 2022
Country/TerritoryChina
CityHangzhou
Period2022/12/172022/12/18

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Graphics and Computer-Aided Design
  • Modeling and Simulation

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