| Full text | |
| Author(s): |
Tinos, Renato
;
Yang, Shengxiang
;
IEEE
Total Authors: 3
|
| Document type: | Journal article |
| Source: | 2008 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-8; v. N/A, p. 2-pg., 2008-01-01. |
| Abstract | |
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) | |