Sobre a convergência de métodos de descida em otimização não-suave: aplicações à ciência comportamental

In this work, we investigate four different types of descent methods: a dual descent method in the scalar context and a multiobjective proximal point methods (one exact and two inexact versions). The first one is restricted to functions that satisfy the Kurdyka-Lojasiewicz property, where it is used...

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Detalles Bibliográficos
Autor: Sousa Júnior, Valdinês Leite de
Tipo de recurso: tesis doctoral
Estado:Versión publicada
Fecha de publicación:2017
País:Brasil
Institución:Universidade Federal de Goiás (UFG)
Repositorio:Repositório Institucional da UFG
Idioma:portugués
OAI Identifier:oai:repositorio.bc.ufg.br:tede/6864
Acceso en línea:http://repositorio.bc.ufg.br/tede/handle/tede/6864
Access Level:acceso abierto
Palabra clave:Métodos de descida
Propriedade Kurdyka-Lojasiewicz
Otimização multiobjetivo
Ciência comportamental
Racionalidade variacional
Método do ponto proximal
Descent methods
Kurdyka-Lojasiewicz property
Multiobjective optimization
Behavioral sciences
Variational rationality
Proximal point method
CIENCIAS EXATAS E DA TERRA::MATEMATICA
Descripción
Sumario:In this work, we investigate four different types of descent methods: a dual descent method in the scalar context and a multiobjective proximal point methods (one exact and two inexact versions). The first one is restricted to functions that satisfy the Kurdyka-Lojasiewicz property, where it is used a quasi-distance as a regularization function. In the next three methods, the objective is to study the convergence of a multiobjective proximal methods (exact an inexact) for a particular class of multiobjective functions that are not necessarily differentiable. For the inexact methods, we choose a proximal distance as the regularization term. Such a well-known distance allows us to analyze the convergence of the method under various settings. Applications in behavioral sciences are analyzed in the sense of the variational rationality approach.