An inexact and nonmonotone proximal method for smooth unconstrained minimization
S. A. Santos (sandraime.unicamp.br)
Abstract: 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.
Keywords: Proximal point algorithms; regularization; nonconvex problems; unconstrained minimization; global convergence; nonmonotone line search; numerical experiments.
Category 1: Nonlinear Optimization (Unconstrained Optimization )
Entry Submitted: 05/24/2013
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