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Global convergence of trust-region algorithms for constrained minimization without derivatives

Paulo D. Conejo(pconejo33***at***gmail.com)
Elizabeth W. Karas(ewkaras***at***gmail.com)
Lucas G. Pedroso(lucaspedroso***at***ufpr.br)
Ademir A. Ribeiro(ademir.ribeiro***at***ufpr.br)
Mael Sachine(mael***at***ufpr.br)

Abstract: In this work we propose a trust-region algorithm for the problem of minimizing a function within a convex closed domain. We assume that the objective function is differentiable but no derivatives are available. The algorithm has a very simple structure and allows a great deal of freedom in the choice of the models. Under reasonable assumptions for derivative-free schemes, we prove global convergence for the algorithm, that is to say, that all accumulation points of the sequence generated by the algorithm are stationary.

Keywords: Derivative-free optimization; constrained optimization; trust region

Category 1: Nonlinear Optimization (Constrained Nonlinear Optimization )

Category 2: Nonlinear Optimization

Citation: Department of Mathematics, Federal University of ParanĂ¡, September, 2012

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Entry Submitted: 09/27/2012
Entry Accepted: 09/27/2012
Entry Last Modified: 09/27/2012

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