A trust region method based on interior point techniques for nonlinear programming

被引：1221

作者：

Byrd, RH ^{[1
]}

Gilbert, JC

Nocedal, J

机构：

[1] Univ Colorado, Dept Comp Sci, Boulder, CO 80309 USA

[2] INRIA Rocquencourt, F-78153 Le Chesnay, France

[3] Northwestern Univ, ECE Dept, Evanston, IL 60208 USA

来源：

MATHEMATICAL PROGRAMMING | 2000年 / 89卷 / 01期

关键词：

constrained optimization; interior point method; large-scale optimization; nonlinear programming; primal method; primal-dual method; SQP iteration; barrier method; trust region method;

D O I：

10.1007/PL00011391

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

An algorithm for minimizing a nonlinear function subject to nonlinear inequality constraints is described. It applies sequential quadratic programming techniques to a sequence of barrier problems, and uses trust regions to ensure the robustness of the iteration and to allow the direct use of second order derivatives. This framework permits primal and primal-dual steps, but the paper focuses on the primal version of the new algorithm. An analysis of the convergence properties of this method is presented.

引用

页码：149 / 185

页数：37

共 29 条

[1]

ANSTREICHER KM, 1994, OPTIMIZATION METHODS, V3, P273

[2]

BLANCHON G, 1996, P 12 POW SYST COMP C

[3]

Byrd R. H., 1987, SIAM C OPT HOUST TX

[4] A TRUST REGION ALGORITHM FOR NONLINEARLY CONSTRAINED OPTIMIZATION [J].