Alternative Mutation Operators in Collaborative Neurodynamic Optimization

Xinqi Li, Jun Wang, Sam Kwong

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

1 Citation (Scopus)

Abstract

Collaborative neurodynamic optimization (CNO) is a global search technique that integrates the neurodynamic optimization with a swarm intelligence algorithm. Diversity is a key point for global optimization. Mutation operator is employed in CNO to ensure diversity. In the existing literature, the diversification performance of different mutation operators is unknown. In this paper, four mutation operators, Gaussian, Cauchy, Levy and wavelet mutations, are analyzed to compare the performances of mutation operators. Simulation results on four benchmark multimodal functions are discussed.

Original languageEnglish
Title of host publication10th International Conference on Information Science and Technology, ICIST 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages126-133
Number of pages8
ISBN (Electronic)9781728155586
DOIs
Publication statusPublished - Sep 2020
Externally publishedYes
Event10th International Conference on Information Science and Technology, ICIST 2020 - Virtual, Bath, London, and Plymouth, United Kingdom
Duration: 9 Sep 202015 Sep 2020

Publication series

Name10th International Conference on Information Science and Technology, ICIST 2020

Conference

Conference10th International Conference on Information Science and Technology, ICIST 2020
Country/TerritoryUnited Kingdom
CityVirtual, Bath, London, and Plymouth
Period9/09/2015/09/20

Keywords

  • collaborative neurodynamic optimization
  • global optimization
  • mutation operator

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