A sequential quadratically constrained quadratic programming method for unconstrained minimax problems

被引：13
|
作者：
Jian, Jin-bao [2 ]
Chao, Mian-tao [1 ]
机构：
[1] Guangxi Coll Educ, Dept Math & Comp Sci, Nanning 530023, Peoples R China
[2] Guangxi Univ, Coll Math & Informat Sci, Nanning 530004, Peoples R China
来源：
JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS | 2010年 / 362卷 / 01期
关键词：
Minimax programs; Quadratic constraints; Quadratic programming; Global convergence; Convergence rate; NONMONOTONE LINE SEARCH; SQP ALGORITHM; CONVERGENCE; OPTIMIZATION; DIRECTIONS;
D O I：
10.1016/j.jmaa.2009.08.046
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, a sequential quadratically constrained quadratic programming (SQCQP) method for unconstrained minimax problems is presented. At each iteration the SQCQP method solves a subproblem that involves convex quadratic inequality constraints and a convex quadratic objective function. The global convergence of the method is obtained under much weaker conditions without any constraint qualification. Under reasonable assumptions, we prove the strong convergence, superlinearly and quadratic convergence rate. (C) 2009 Elsevier Inc. All rights reserved.
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页码：34 / 45
页数：12
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