Volume 23, Issue 2
A Revised Conjugate Gradient Projection Algorithm for Inequality Constrained Optimizations

J. Comp. Math., 23 (2005), pp. 217-224.

Published online: 2005-04

Preview Full PDF 260 2220
Export citation

Cited by

• 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.

• Keywords

Constrained optimization, Conjugate gradient projection, Revised direction, Superlinear convergence.

• BibTex
• RIS
• TXT
@Article{JCM-23-217, author = {}, title = {A Revised Conjugate Gradient Projection Algorithm for Inequality Constrained Optimizations}, journal = {Journal of Computational Mathematics}, year = {2005}, volume = {23}, number = {2}, pages = {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.

}, issn = {1991-7139}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jcm/8810.html} }
TY - JOUR T1 - A Revised Conjugate Gradient Projection Algorithm for Inequality Constrained Optimizations JO - Journal of Computational Mathematics VL - 2 SP - 217 EP - 224 PY - 2005 DA - 2005/04 SN - 23 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jcm/8810.html KW - Constrained optimization, Conjugate gradient projection, Revised direction, Superlinear convergence. AB -

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.

Wei Wang, Lian-Sheng Zhang & Yi-Fan Xu. (1970). A Revised Conjugate Gradient Projection Algorithm for Inequality Constrained Optimizations. Journal of Computational Mathematics. 23 (2). 217-224. doi:
Copy to clipboard
The citation has been copied to your clipboard