Particle swarm optimization with variable population size

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Detalles Bibliográficos
Autor Principal: Lanzarini, Laura Cristina
Otros autores o Colaboradores: Leza, María Victoria, De Giusti, Armando Eduardo
Formato: Capítulo de libro
Lengua:inglés
Temas:
COMPUTACIÓN EVOLUTIVA
OPTIMIZACIÓN
MÉTODOS HEURÍSTICOS
Acceso en línea:http://dx.doi.org/10.1007/978-3-540-69731-2_43
Consultar en el Cátalogo
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.
Notas:Formato de archivo: PDF. -- Este documento es producción intelectual de la Facultad de Informática - UNLP (Colección BIPA/Biblioteca)
Descripción Física:1 archivo (437,6 KB)
DOI:10.1007/978-3-540-69731-2_43

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520 |a 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. 
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