Failure of global convergence for a class of interior point methods for nonlinear programming

被引：0
|
作者：
Andreas Wächter
Lorenz T. Biegler
机构：
[1] Department of Chemical Engineering,
[2] Carnegie Mellon University,undefined
[3] Pittsburgh,undefined
[4] PA 15213,undefined
[5] USA,undefined
[6] e-mail: {andreasw,undefined
[7]  lb01}@andrew.cmu.edu,undefined
来源：
Mathematical Programming | 2000年 / 88卷
关键词：
Key words: nonlinear optimization – interior point methods – global convergence – Newton’s method; Mathematics Subject Classification (1991): 65K05, 90G30, 90G51;
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学科分类号：
摘要：
Using a simple analytical example, we demonstrate that a class of interior point methods for general nonlinear programming, including some current methods, is not globally convergent. It is shown that those algorithms produce limit points that are neither feasible nor stationary points of some measure of the constraint violation, when applied to a well-posed problem.
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页码：565 / 574
页数：9
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