GAAP. Genetic algorithm with auxiliary populations applied to continuous optimization problems

Título:

GAAP. Genetic algorithm with auxiliary populations applied to continuous optimization problems

Autor:

Corbalán, Leonardo César

Colaboradores:

; Hasperué, Waldo; Lanzarini, Laura Cristina

Temas:

OPTIMIZACIÓN

En:

International Conference on Information Technology Interfaces (34ª : 2012 jun. 25-28 : Cavtat, Croacia). Proceedings. IEEE, 2012, pp. 411-416

Resumen:

Genetic algorithms have been used successfully to solve continuous optimization problems. However, an early convergence to low-quality solutions is one of the most common difficulties encountered when using these strategies. In this paper, a method that combines multiple auxiliary populations with the main population of the algorithm is proposed. The role of the auxiliary populations is dual: to prevent or hinder the early convergence to local suboptimal solutions, and to provide a local search mechanism for a greater exploitation of the most promising regions within the search space.

URL/DOI:

http://dx.doi.org/10.2498/iti.2012.0382

Medio:

Soporte electrónico

Tipo de documento:

Artículo

Descripción física:

1 archivo (154,9 KB)

Idioma:

Inglés

Publicación:

IEEE Press, 2012

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