Nonlinear programming without a penalty function or a filter

被引：68

作者：

Gould, N. I. M. ^{[2
]}

Toint, Ph. L. ^{[1
]}

机构：

[1] FUNDP Univ Namur, Dept Math, B-5000 Namur, Belgium

[2] Univ Oxford, Comp Lab, Oxford OX1 3QD, England

来源：

MATHEMATICAL PROGRAMMING | 2010年 / 122卷 / 01期

基金：

英国工程与自然科学研究理事会;

关键词：

Nonlinear optimization; Equality constraints; Numerical algorithms; Global convergence; CONSTRAINED OPTIMIZATION; GLOBAL CONVERGENCE; ALGORITHM; EQUALITY;

D O I：

10.1007/s10107-008-0244-7

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

A new method is introduced for solving equality constrained nonlinear optimization problems. This method does not use a penalty function, nor a filter, and yet can be proved to be globally convergent to first-order stationary points. It uses different trust-regions to cope with the nonlinearities of the objective function and the constraints, and allows inexact SQP steps that do not lie exactly in the nullspace of the local Jacobian. Preliminary numerical experiments on CUTEr problems indicate that the method performs well.

引用

页码：155 / 196

页数：42

共 27 条

[1] A REDUCED HESSIAN METHOD FOR LARGE-SCALE CONSTRAINED OPTIMIZATION [J].