-

 

 

 




Optimization Online





 

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

Download: [PDF]

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

Modify/Update this entry


  Visitors Authors More about us Links
  Subscribe, Unsubscribe
Digest Archive
Search, Browse the Repository

 

Submit
Update
Policies
Coordinator's Board
Classification Scheme
Credits
Give us feedback
Optimization Journals, Sites, Societies
Mathematical Optimization Society