A Primaldual Interior Method for Nonconvex Nonlinear Programming
 David M. Gay,
 Michael L. Overton,
 Margaret H. Wright
 … show all 3 hide
Abstract
Primaldual interior methods for nonconvex nonlinear programming have recently been the subject of significant attention from the optimization community. Several different primaldual methods have been suggested, along with some theoretical and numerical results. Although the underlying motivation for all of these methods is relatively uniform, there axe nonetheless substantive variations in crucial details, including the formulation of the nonlinear equations, the form of the associated linear system, the choice of linear algebraic procedures for solving this system, strategies for adjusting the barrier parameter and the Lagrange multiplier estimates, the merit function, and the treatment of indefiniteness. Not surprisingly, each of these choices can affect the theoretical properties and practical performance of the method. This paper discusses the approaches to these issues that we took in implementing a specific primaldual method.
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 Title
 A Primaldual Interior Method for Nonconvex Nonlinear Programming
 Book Title
 Advances in Nonlinear Programming
 Book Subtitle
 Proceedings of the 96 International Conference on Nonlinear Programming
 Book Part
 II
 Pages
 pp 3156
 Copyright
 1998
 DOI
 10.1007/9781461333357_2
 Print ISBN
 9781461333371
 Online ISBN
 9781461333357
 Series Title
 Applied Optimization
 Series Volume
 14
 Series ISSN
 13846485
 Publisher
 Springer US
 Copyright Holder
 SpringerVerlag US
 Additional Links
 Topics
 Industry Sectors
 eBook Packages
 Editors

 Yaxiang Yuan ^{(2)}
 Editor Affiliations

 2. Institute of Computational Mathematics, and Scientific/Engineering Computing, Chinese Academy of Sciences
 Authors

 David M. Gay ^{(3)}
 Michael L. Overton ^{(4)}
 Margaret H. Wright ^{(3)}
 Author Affiliations

 3. Bell Laboratories, Murray Hill, New Jersey, 07974, USA
 4. New York University, New York, New York, 10012, USA
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