A Revised Conjugate Gradient Projection Algorithm for Inequality Constrained Optimizations

A Revised Conjugate Gradient Projection Algorithm for Inequality Constrained Optimizations

Year:    2005

Journal of Computational Mathematics, Vol. 23 (2005), Iss. 2 : pp. 217–224

Abstract

A revised conjugate gradient projection method for nonlinear inequality constrained optimization problems is proposed in the paper, since the search direction is the combination of the conjugate projection gradient and the quasi-Newton direction. It has two merits. The one is that the amount of computation is lower because the gradient matrix only needs to be computed one time at each iteration. The other is that the algorithm is of global convergence and locally superlinear convergence without strict complementary condition under some mild assumptions. In addition, the search direction is explicit.

You do not have full access to this article.

Already a Subscriber? Sign in as an individual or via your institution

Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/2005-JCM-8810

Journal of Computational Mathematics, Vol. 23 (2005), Iss. 2 : pp. 217–224

Published online:    2005-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    8

Keywords:    Constrained optimization Conjugate gradient projection Revised direction Superlinear convergence.