An efficient sequential quadratic programming algorithm for nonlinear programming

被引：21
|
作者：
Zhu, ZB [1 ]
机构：
[1] Guilin Inst Elect Technol, Dept Computat Sci & Math, Guilin 541004, Peoples R China
来源：
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS | 2005年 / 175卷 / 02期
基金：
中国国家自然科学基金;
关键词：
inequality constrained optimization; method of feasible direction; SQP algorithm; global convergence; superlinear convergence rate;
D O I：
10.1016/j.cam.2004.07.001
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, a new feasible sequential quadratic programming (FSQP) algorithm is proposed to solve the nonlinear programming, where a feasible descent direction is obtained by solving only one QP subproblem. In order to avoid Maratos effect, a high-order revised direction is computed by solving a linear system with involving some "active" constraints. The theoretical analysis shows that global and superlinear convergence can be deduced. (C) 2004 Elsevier B.V. All rights reserved.
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页码：447 / 464
页数：18
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