Paper Info
Title
Multidimensional Mutations In Evolutionary Algorithms Based On Real-Valued Representation
Abstract
This work is focused on the fact that the most probable distance of mutated points in multi- dimensional Gaussian and Cauchy mutations is not in a close neighborhood of the origin, but at a certain distance from it. In the case of the Gaussian mutation, this distance is proportional to the norm of the standard deviation vector and increases with the landscape dimension. This may cause a decrease in the sensitivity of the evolutionary algorithm to narrow peaks when the landscape dimension increases, but, simultaneously, it strengthens the exploration property of the algorithm. Moreover, the influence of the reference frame orientation on the effectiveness of the non- spherical multi- dimensional Cauchy mutation is analyzed using simulation experiments. Four multi- dimensional mutations ( Gaussian, modified Gaussian, non- spherical and spherical Cauchy mutations) are applied to two classes of evolutionary algorithms based on real- valued representation, i. e. Galar's evolutionary search with soft selection and evolutionary programming. A comparative analysis is provided for convergence to the local optimum, sensitivity to narrow peaks, saddle crossing and symmetry problems.
Year
DOI
Venue
2003
10.1080/00207720310001614105
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
Keywords
Field
DocType
reference frame,simulation experiment,standard deviation,comparative analysis,evolutionary algorithm,evolutionary programming
Reference frame,Gaussian mutation,Mathematical optimization,Evolutionary algorithm,Cauchy distribution,Gaussian,Cauchy mutation,Standard deviation,Mathematics
Journal
Volume
Issue
ISSN
34
7
0020-7721
Citations 
PageRank 
References 
6
0.47
4
Authors
1
Name
Order
Citations
PageRank
Andrzej Obuchowicz17610.10