Constraint qualification in a general class of nondifferentiable mathematical programming problems

被引:1
|
作者
Zheng, Xiaojin
Xu, Zengkun
Li, Cheng
机构
[1] Zhejiang Normal Univ, Sch Math Phys & Informat Engn, Jinhua Zhejiang 321004, Peoples R China
[2] Jinhua Coll Profess & Technol, Normal Sch, Jinhua Zhejiang 321017, Peoples R China
关键词
generalized gradient; constraint qualifications; nondifferentiable problems; fractional programming; necessary optimality conditions;
D O I
10.1016/j.camwa.2006.05.018
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The Kuhn-Tucker type necessary optimality conditions are given for the problem of minimizing a local Lipschitzian function subject to a set of differentiable nonlinear inequalities on a convex subset C of R-n, under the conditions of the generalized Kuhn-Tucker constraint qualification or the generalized Arrow-Hurwicz-Uzawa constraint qualification. The case when the set C is open is shown to be a special one of our results, which helps us to improve some of the existing results in the literature. What's more, the case when the object function is the sum of a differentiable function and a convex function is also the special case of our results. Finally, the case when the object function is the quotient of two Lipschitz functions is the special case of our results too. (c) 2007 Elsevier Ltd. All rights reserved.
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页码:21 / 27
页数:7
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