DocumentCode
768714
Title
Directed variation in evolution strategies
Author
Zhou, Qing ; Li, Yanda
Volume
7
Issue
4
fYear
2003
Firstpage
356
Lastpage
366
Abstract
Biological evolution gives rise to self-organizing phenomena. Inspired by this theory, directed variation is added to the (μ, λ) evolution strategies (ES) algorithm and it is called directed variation ES (DVES). In DVES, some neighboring individuals in the population mutate correlatively according to the distribution of the whole population. Experimental results showed that, with the same number of function evaluations, directed variation ES reached better optimization results for different generally used strategies under the ES framework. Experimental analysis showed that the application of directed variation could increase the expected fitness improvement and the probability of fitness improvement. From a biological perspective, directed variation can be regarded as a result of self-organizing evolution.
Keywords
evolutionary computation; self-adjusting systems; (μ, λ) evolution strategies algorithm; DVES; correlative mutation; directed variation ES; directed variation evolution strategies; function evaluations; self-organizing evolution; self-organizing phenomena; Automation; Covariance matrix; Evolution (biology); Evolutionary computation; Functional programming; Gaussian distribution; Genetic mutations; Genetic programming; Iterative algorithms; Probability distribution;
fLanguage
English
Journal_Title
Evolutionary Computation, IEEE Transactions on
Publisher
ieee
ISSN
1089-778X
Type
jour
DOI
10.1109/TEVC.2003.812215
Filename
1223576
Link To Document