A niching co-swarm gravitational search algorithm for multi-modal optimization

Anupam Yadav, Joong Hoon Kim

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In this paper, a Niching co-swarm gravitational search algorithm (CoGSA) is designed for solving multi-modal optimization problems. The collective approach of Gravitational Search Algorithm and differential evolution (DE) is used to solve multi-modal optimization problems. A set of twelve multi-modal problems are taken from a benchmark set of CEC 2013. An experimental study has been performed to evaluate the availability of CoGSA over these twelve problems. The performance is measured in an advanced way. It has been observed that CoGSA provides good solution for multi-modal optimization problems.

Original languageEnglish
Pages (from-to)599-607
Number of pages9
JournalAdvances in Intelligent Systems and Computing
Volume335
DOIs
Publication statusPublished - 2015

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Keywords

  • Differential evolution
  • Gravitational search algorithm
  • Multi-modal
  • Optimization

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

A niching co-swarm gravitational search algorithm for multi-modal optimization. / Yadav, Anupam; Kim, Joong Hoon.

In: Advances in Intelligent Systems and Computing, Vol. 335, 2015, p. 599-607.

Research output: Contribution to journalArticle

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