PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Urfalioglu O., Cetin E. A., Kuruoglu E. E. Levy walk evolution for global optimization. In: GECCO - Genetic and evolutionary computation conference (Atlanta, Georgia, USA, 12-16 Luglio 2008). Proceedings, pp. 537 - 538. ACM, 2008.
 
 
Abstract
(English)
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.
URL: http://delivery.acm.org/10.1145/1390000/1389200/p537-urfalioglu.pdf?key1=1389200&key2=9607745221&coll=GUIDE&dl=GUIDE&CFID=8609639&CFTOKEN=63976129
Subject Levy walk
Global optimisation
G.1.6 Optimization. Stochastic programming
60G50 Sums of independent random variables; random walks
78M50 Optimization


Icona documento 1) Download Document PDF


Icona documento Open access Icona documento Restricted Icona documento Private

 


Per ulteriori informazioni, contattare: Librarian http://puma.isti.cnr.it

Valid HTML 4.0 Transitional