Differential evolution with adaptive population size

Edwin C. Shi, Hung Fat Frank Leung, Bonnie N.F. Law

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Differential Evolution (DE) is one of the evolutionary algorithms under active research. It has been successfully applied to many real-world problems. The performance of DE highly depends on the population size Np. An improper selection of Np may result in premature convergence or waste of computational resources. In this paper, we proposed a novel method to adaptively control the population size of DE. With this method users do not need to set the Np parameter for DE. The proposed algorithm DEAPS is compared with the conventional DE with different population sizes. DEAPS demonstrates encouraging results on its capability of adaption for seven problems of benchmark test functions.
Original languageEnglish
Title of host publication2014 19th International Conference on Digital Signal Processing, DSP 2014
PublisherIEEE
Pages876-881
Number of pages6
Volume2014-January
ISBN (Electronic)9781479946129
DOIs
Publication statusPublished - 1 Jan 2014
Event2014 19th International Conference on Digital Signal Processing, DSP 2014 - Hong Kong, Hong Kong
Duration: 20 Aug 201423 Aug 2014

Conference

Conference2014 19th International Conference on Digital Signal Processing, DSP 2014
Country/TerritoryHong Kong
CityHong Kong
Period20/08/1423/08/14

Keywords

  • Differential evolution
  • Population size adaptation

ASJC Scopus subject areas

  • Signal Processing

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