UNCONSTRAINED LAGRANGIANS IN NONLINEAR-PROGRAMMING

被引：45

作者：

MANGASARIAN, OL ^{[1
]}

机构：

[1] UNIV WISCONSIN,DEPT COMP SCI,MADISON,WI 53706

来源：

SIAM JOURNAL ON CONTROL | 1975年 / 13卷 / 04期

关键词：

D O I：

10.1137/0313045

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A wide class of Lagrangian functions is associated with a nonconvex, inequality and equality constrained optimization problem in such a way that unconstrained stationary points and local saddle points of each Lagrangian are related to Kuhn-Tucker points or local or global solutions of the optimization problem. As a consequence, duality results and two computational algorithms for solving the optimization problem are obtained. One algorithm is a Newton algorithm which has a local superlinear or quadratic rate of convergence. The other method is a locally linearly convergent method for finding stationary points of the Lagrangian and is an extension of the method of multipliers of Hestenes and Powell to inequalities.

引用

页码：772 / 791

页数：20

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