A Nonmonotonic Trust Region Technique for Nonlinear Constrained Optimization

A Nonmonotonic Trust Region Technique for Nonlinear Constrained Optimization

Year:    1995

Author:    De-Tong Zhu

Journal of Computational Mathematics, Vol. 13 (1995), Iss. 1 : pp. 20–31

Abstract

In this paper, a nonmonotonic trust region method for optimization problems with equality constraints is proposed by introducing a nonsmooth merit function and adopting a correction step. It is proved that all accumulation points of the iterates generated by the proposed algorithm are Kuhn-Tucker points and that the algorithm is $q$-superlinearly convergent.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/1995-JCM-9248

Journal of Computational Mathematics, Vol. 13 (1995), Iss. 1 : pp. 20–31

Published online:    1995-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    12

Keywords:   

Author Details

De-Tong Zhu