Adaptive differential evolution: A visual comparison

Chi An Chen, Tsung Che Chiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Differential evolution (DE) is a variant of the evolutionary algorithm and has good performance in solving continuous optimization problems. Two important parameters, F and CR, control the behaviors of the mutation and crossover operators in DE. Setting their values is critical, but the tuning process could be difficult and time-consuming. In the last decade, many adaptive DE have been proposed with various mechanisms to adjust the parameter values during the evolutionary process. Although these studies conducted numerical experiments and showed promising performance of the proposed algorithms, very few studies investigated and compared how the parameter values are adjusted by these algorithms. In this study, we compared six different types of adaptive DEs and observed their behaviors visually. Several interesting observations are made.

Original languageEnglish
Title of host publication2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages401-408
Number of pages8
ISBN (Electronic)9781479974924
DOIs
Publication statusPublished - 2015 Sep 10
EventIEEE Congress on Evolutionary Computation, CEC 2015 - Sendai, Japan
Duration: 2015 May 252015 May 28

Publication series

Name2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings

Other

OtherIEEE Congress on Evolutionary Computation, CEC 2015
CountryJapan
CitySendai
Period15/5/2515/5/28

Keywords

  • Visualization
  • adaptive
  • comparison
  • differential evolution
  • parameter control

ASJC Scopus subject areas

  • Computer Science Applications
  • Computational Mathematics

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  • Cite this

    Chen, C. A., & Chiang, T. C. (2015). Adaptive differential evolution: A visual comparison. In 2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings (pp. 401-408). [7256918] (2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEC.2015.7256918