An inexact and nonmonotone proximal method for smooth unconstrained minimization

Autor(es)

Santos, S. A. ^[1] ; Silva, R. C. M. ^[2]

Afiliação do(s) autor(es)

^[1] Univ Estadual Campinas, Dept Appl Math, Sao Paulo - Brazil

^[2] Univ Fed Amazonas, Dept Math, Manaus, Amazonas - Brazil

• Tipo de documento: Artigo Científico
• Fonte: Journal of Computational and Applied Mathematics; v. 269, p. 86-100, OCT 15 2014.
• Citações Web of Science: 6

Resumo

An implementable proximal point algorithm is established for the smooth nonconvex unconstrained minimization problem. At each iteration, the algorithm minimizes approximately a general quadratic by a truncated strategy with step length control. The main contributions are: (i) a framework for updating the proximal parameter; (ii) inexact criteria for approximately solving the subproblems; (iii) a nonmonotone criterion for accepting the iterate. The global convergence analysis is presented, together with numerical results that validate and put into perspective the proposed approach. (C) 2014 Elsevier B.V. All rights reserved. (AU)

• Processo FAPESP: 13/07375-0 - CeMEAI - Centro de Ciências Matemáticas Aplicadas à Indústria
• Beneficiário: Francisco Louzada Neto
• Modalidade de apoio: Auxílio à Pesquisa - Centros de Pesquisa, Inovação e Difusão - CEPIDs
• Processo FAPESP: 13/05475-7 - Métodos computacionais de otimização
• Beneficiário: Sandra Augusta Santos
• Modalidade de apoio: Auxílio à Pesquisa - Temático