Newton-type methods for nonlinearly constrained programming problems-algorithms and theory

For optimization problems including inequality constraints the well-known locally and superlinealy convergent methods of Levitin/Polyak, of Robinson and of Wilson (Recursive Quadratic Programming) lead to inequality constrained nonlinear subproblems. In the present paper optimization methods are int...

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Bibliographic Details
Published in:	Optimization Vol. 19; no. 3; pp. 397 - 412
Main Authors:	Kleinmichel, H., Schönefeld, K.
Format:	Journal Article
Language:	English
Published:	Akademic-Verlag 01.01.1988
Subjects:	locally superlinearly convergent algorithms Nonlinear programming algorithms Primary:65 K 05 Primary:90 C 30
ISSN:	0233-1934, 1029-4945
Online Access:	Get full text
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Summary:	For optimization problems including inequality constraints the well-known locally and superlinealy convergent methods of Levitin/Polyak, of Robinson and of Wilson (Recursive Quadratic Programming) lead to inequality constrained nonlinear subproblems. In the present paper optimization methods are introduced which are also locally and superlinearly convergent, but in contrast to the methods mentioned above the occurring subproblems are systems of linear equations. This results from the fact that the methods proposed are based on Newton's method for solving nonlinear equations.
ISSN:	0233-1934 1029-4945
DOI:	10.1080/02331938808843355