Elite-of-the-Elites Driven Five-Layered Gravitational Search Algorithm for Optimization

Lin Zhong, Qingya Sui, Jiatianyi Yu, Rong Long Wang, Zhenyu Lei, Shangce Gao*

*Corresponding author for this work

Research output: Contribution to journalLetterpeer-review

3 Scopus citations

Abstract

The gravitational search algorithm (GSA) is a popular optimization method inspired by celestial interactions. And the MLGSA is an outstanding variant of GSA. To improve its performance, we propose the elite-of-the-elites driven five-layered gravitational search algorithm (EFGSA). EFGSA introduces a new population layer comprising elite individuals, improving the balance between exploration and exploitation. Experimental results on the 2017 IEEE Conference on Evolutionary Computation (CEC) benchmark functions demonstrate EFGSA's superiority over the MLGSA algorithm in terms of solution quality and convergence speed. The obtained results underscore the efficacy of EFGSA in addressing optimization problems.

Original languageEnglish
Pages (from-to)1958-1960
Number of pages3
JournalIEEJ Transactions on Electrical and Electronic Engineering
Volume18
Issue number12
DOIs
StatePublished - 2023/12

Keywords

  • evolutionary algorithm
  • exploration and exploitation
  • gravitational search algorithm
  • population structure

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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