| Texto completo | |
| Autor(es): |
Tinos, Renato
;
Yang, Shengxiang
;
IEEE
Número total de Autores: 3
|
| Tipo de documento: | Artigo Científico |
| Fonte: | 2008 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-8; v. N/A, p. 2-pg., 2008-01-01. |
| Resumo | |
The use of evolutionary programming algorithms with self-adaptation of the mutation distribution for dynamic optimization problems is investigated in this paper. In the proposed method, the q-Gaussian distribution is employed to generate new candidate solutions by mutation. A real parameter q, which defines the shape of the distribution, is encoded in the chromosome of individuals and is allowed to evolve. Algorithms with self-adapted mutation generated from isotropic and anisotropic distributions are presented. In the experimental study, the q-Gaussian mutation is compared to Gaussian and Cauchy mutation on three dynamic optimization problems. (AU) | |
| Processo FAPESP: | 04/04289-6 - Algoritmos evolucionários e redes neurais artificiais em problemas não-estacionários |
| Beneficiário: | Renato Tinós |
| Modalidade de apoio: | Auxílio à Pesquisa - Jovens Pesquisadores |