Levy walk evolution for global optimization
Urfalioglu O., Cetin E., Kuruoglu E. E.
Levy walk Global optimisation
A novel evolutionary global optimization approach based on adaptive covariance estimation is proposed. The proposed method samples from a multivariate Levy Skew Alpha-Stable distribution with the estimated covariance matrix to realize a random walk and so to generate new solution candidates in the mutation step. The proposed method is compared to the popular Di erential Evolution method, which is one of the best general evolutionary global optimizers available. Experimental results indicate that the proposed approach yields a general improvement in the required number of function evaluations to solve global optimization problems. Especially, as shown in experiments, the underlying heavy tailed alpha-stable distribution enables a considerably more e ective global search in more complex problems.
Source: Genetic and evolutionary computation conference, pp. 537–538, Atlanta, Georgia, USA, 12-16 Luglio 2008
Publisher: ACM Press, New York, USA
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@inproceedings{oai:it.cnr:prodotti:91864,
title = {Levy walk evolution for global optimization},
author = {Urfalioglu O. and Cetin E. and Kuruoglu E. E.},
publisher = {ACM Press, New York, USA},
booktitle = {Genetic and evolutionary computation conference, pp. 537–538, Atlanta, Georgia, USA, 12-16 Luglio 2008},
year = {2008}
}
0000-0002-2608-8034