Soft Computing

, Volume 9, Issue 6, pp 448–462

A Fuzzy Adaptive Differential Evolution Algorithm


DOI: 10.1007/s00500-004-0363-x

Cite this article as:
Liu, J. & Lampinen, J. Soft Comput (2005) 9: 448. doi:10.1007/s00500-004-0363-x


The differential evolution algorithm is a floating-point encoded evolutionary algorithm for global optimization over continuous spaces. The algorithm has so far used empirically chosen values for its search parameters that are kept fixed through an optimization process. The objective of this paper is to introduce a new version of the Differential Evolution algorithm with adaptive control parameters – the fuzzy adaptive differential evolution algorithm, which uses fuzzy logic controllers to adapt the search parameters for the mutation operation and crossover operation. The control inputs incorporate the relative objective function values and individuals of the successive generations. The emphasis of this paper is analysis of the dynamics and behavior of the algorithm. Experimental results, provided by the proposed algorithm for a set of standard test functions, outperformed those of the standard differential evolution algorithm for optimization problems with higher dimensionality.


Differential evolutionEvolutionary algorithmsFuzzy logic control

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  1. 1.Laboratory of Information ProcessingLappeenranta University of TechnologyLappeenrantaFinland