A fuzzy adaptive differential evolution algorithm

被引：706

作者：

Liu, J ^{[1
]}

Lampinen, J ^{[1
]}

机构：

[1] Lappeenranta Univ Technol, Lab Informat Proc, FIN-53851 Lappeenranta, Finland

来源：

SOFT COMPUTING | 2005年 / 9卷 / 06期

关键词：

differential evolution; evolutionary algorithms; fuzzy logic control;

D O I：

10.1007/s00500-004-0363-x

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：448 / 462

页数：15

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