Cooperative Coevolutionary Particle Swarms using Fuzzy Logic for Large Scale Optimization

A cooperative coevolutionary framework can improve the performance of optimization algorithms on large-scale problems. In this paper, we propose a new Cooperative Coevolutionary algorithm to improve our preliminary work, FuzzyPSO2. This new proposal, called CCFPSO, uses the random grouping technique...

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Detalles Bibliográficos
Autores principales:	Paz, Fabiola, Leguizamón, Guillermo, Mezura Montes, Efrén
Formato:	Articulo
Lenguaje:	Inglés
Publicado:	2021
Materias:	Ciencias Informáticas Adaptive inertia weight Cooperative coevolutionary Fuzzy logic Particle Swann Optimization Coevolución cooperativa Lógica borrosa Optimización por enjambre de partículas Peso de inercia adaptativo
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/128261
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

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institution	Universidad Nacional de La Plata
institution_str	I-19
repository_str	R-120
collection	SEDICI (UNLP)
language	Inglés
topic	Ciencias Informáticas Adaptive inertia weight Cooperative coevolutionary Fuzzy logic Particle Swann Optimization Coevolución cooperativa Lógica borrosa Optimización por enjambre de partículas Peso de inercia adaptativo
spellingShingle	Ciencias Informáticas Adaptive inertia weight Cooperative coevolutionary Fuzzy logic Particle Swann Optimization Coevolución cooperativa Lógica borrosa Optimización por enjambre de partículas Peso de inercia adaptativo Paz, Fabiola Leguizamón, Guillermo Mezura Montes, Efrén Cooperative Coevolutionary Particle Swarms using Fuzzy Logic for Large Scale Optimization
topic_facet	Ciencias Informáticas Adaptive inertia weight Cooperative coevolutionary Fuzzy logic Particle Swann Optimization Coevolución cooperativa Lógica borrosa Optimización por enjambre de partículas Peso de inercia adaptativo
description	A cooperative coevolutionary framework can improve the performance of optimization algorithms on large-scale problems. In this paper, we propose a new Cooperative Coevolutionary algorithm to improve our preliminary work, FuzzyPSO2. This new proposal, called CCFPSO, uses the random grouping technique that changes the size of the subcomponents in each generation. Unlike FuzzyPSO2, CCFPSO’s re-initialization of the variables, suggested by the fuzzy system, were performed on the particles with the worst fitness values. In addition, instead of updating the particles based on the global best particle, CCFPSO was updated considering the personal best particle and the neighborhood best particle. This proposal was tested on large-scale problems that resemble real-world problems (CEC2008, CEC2010), where the performance of CCFPSO was favorable in comparison with other state-of-the-art PSO versions, namely CCPSO2, SLPSO, and CSO. The experimental results indicate that using a Cooperative Coevolutionary PSO approach with a fuzzy logic system can improve results on high dimensionality problems (100 to 1000 variables).
format	Articulo Articulo
author	Paz, Fabiola Leguizamón, Guillermo Mezura Montes, Efrén
author_facet	Paz, Fabiola Leguizamón, Guillermo Mezura Montes, Efrén
author_sort	Paz, Fabiola
title	Cooperative Coevolutionary Particle Swarms using Fuzzy Logic for Large Scale Optimization
title_short	Cooperative Coevolutionary Particle Swarms using Fuzzy Logic for Large Scale Optimization
title_full	Cooperative Coevolutionary Particle Swarms using Fuzzy Logic for Large Scale Optimization
title_fullStr	Cooperative Coevolutionary Particle Swarms using Fuzzy Logic for Large Scale Optimization
title_full_unstemmed	Cooperative Coevolutionary Particle Swarms using Fuzzy Logic for Large Scale Optimization
title_sort	cooperative coevolutionary particle swarms using fuzzy logic for large scale optimization
publishDate	2021
url	http://sedici.unlp.edu.ar/handle/10915/128261
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Cooperative Coevolutionary Particle Swarms using Fuzzy Logic for Large Scale Optimization

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