Modified self-adaptive strategy for controlling parameters in differential evolution

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


In this paper, we propose a new technical to modify the self-adaptive Strategy for Controlling Parameters in Differential Evolution algorithm (MSADE). The DE algorithm has been used in many practical cases and has demonstrated good convergence properties. It has only a few control parameters as NP (Number of Particles), F (scaling factor) and CR (crossover), which are kept fixed throughout the entire evolutionary process. However, these control parameters are very sensitive to the setting of the control parameters based on their experiments. The value of control parameters depend on the characteristics of each objective function, so we have to tune their value in each problem that mean it will take too long time to perform. We present a new version of the DE algorithm for obtaining self-adaptive control parameter settings that show good performance on numerical benchmark problems.

Original languageEnglish
Title of host publicationAsiaSim 2012 - Asia Simulation Conference 2012, Proceedings
Number of pages9
EditionPART 2
Publication statusPublished - 2012 Nov 7
EventAsia Simulation Conference, AsiaSim 2012 - Shanghai, China
Duration: 2012 Oct 272012 Oct 30

Publication series

NameCommunications in Computer and Information Science
NumberPART 2
Volume324 CCIS
ISSN (Print)1865-0929


ConferenceAsia Simulation Conference, AsiaSim 2012


  • Differential Evolution (DE)
  • Global search
  • Local search
  • Multi-peak problems

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics


Dive into the research topics of 'Modified self-adaptive strategy for controlling parameters in differential evolution'. Together they form a unique fingerprint.

Cite this