A sufficient and necessary condition for nonconvex constrained optimization

被引：15

作者：

Goh, CJ

Yang, XQ

机构：

[1] Department of Mathematics, University of Western Australia, Nedlands

来源：

APPLIED MATHEMATICS LETTERS | 1997年 / 10卷 / 05期

基金：

澳大利亚研究理事会;

关键词：

inequality constraints; nonconvex optimization; equivalent optimality condition;

D O I：

10.1016/S0893-9659(97)00075-X

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

The conventional Lagrangian approach to solving constrained optimization problems leads to optimality conditions which are either necessary, or sufficient? but not both unless the underlying cost and constraint functions are also convex. We introduce a new approach based on the Tchebyshev norm. This leads to an optimality condition which is both sufficient and necessary, without any convexity assumption. This optimality condition can be used to devise a conceptually simple method for solving nonconvex inequality constrained optimization problems.

引用

页码：9 / 12

页数：4