Particle swarm optimization with variable population size

Título:

Particle swarm optimization with variable population size

Autor:

Lanzarini, Laura Cristina

Colaboradores:

; Leza, María Victoria; De Giusti, Armando Eduardo

Temas:

COMPUTACIÓN EVOLUTIVAOPTIMIZACIÓNMÉTODOS HEURÍSTICOS

En:

Artificial Intelligence and Soft Computing - ICAISC 2008 : 9th International Conference Zakopane, Poland, June 22-26, 2008 Proceedings. Berlín : Springer, 2008. (Lecture Notes in Computer Science ; 5097), pp. 438-449

Resumen:

At present, the optimization problem resolution is a topic of great interest, which has fostered the development of several computer methods forsolving them. Particle Swarm Optimization (PSO) is a metaheuristics which has successfully been used in the resolution of a wider range of optimization problems, including neural network training and function minimization. In its original definition, PSO makes use, during the overall adaptive process, of a population made up by a fixed number of solutions. This paper presents a new extension of PSO, called VarPSO, incor- porating the concepts of age and neighborhood to allow varying the size of the population. In this way, the quality of the solution to be obtained will not be affected by the used swarms size. The method here proposed is applied to the resolution of some com- plex functions, finding better results than those typically achieved using a fixed size population.

URL/DOI:

http://dx.doi.org/10.1007/978-3-540-69731-2_43

Medio:

Soporte electrónico

Tipo de documento:

Artículo

Descripción física:

1 archivo (437,6 KB)

Idioma:

Inglés

Publicación:

Springer-Verlag, 2008

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