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Interior point methods of mathematical programming

Author: Tamás Terlaky
Publisher: Dordrecht, Netherlands ; Boston : Kluwer, ©1996.
Series: Applied optimization, v. 5.
Edition/Format:   Print book : EnglishView all editions and formats
Summary:
The book provides an overview of the research in interior point methods since the publication of N. Karmarkar's seminal paper in 1984. Leading international experts have contributed to the book with summaries of their relevant areas of specialization. Part I gives an overview of basic variants of interior point algorithms for linear programming. Duality-theory for LP and sensitivity analysis is developed. Results on  Read more...
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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Tamás Terlaky
ISBN: 0792342011 9780792342014
OCLC Number: 35084922
Description: xxi, 528 pages : illustrations ; 25 cm.
Contents: 1. Introduction to the Theory of Interior Point Methods / Benjamin Jansen, Cornelis Roos and Tamas Terlaky --
2. Affine Scaling Algorithm / Takashi Tsuchiya --
3. Target-Following Methods for Linear Programming / Benjamin Jansen, Cornelis Roos and Tamas Terlaky --
4. Potential Reduction Algorithms / Kurt M. Anstreicher --
5. Infeasible-Interior-Point Algorithms / Shinji Mizuno --
6. Implementation of Interior-Point Methods for Large Scale Linear Programs / Erling D. Andersen, Jacek Gondzio, Csaba Meszaros and Xiaojie Xu --
7. Interior-Point Methods for Classes of Convex Programs / Florian Jarre --
8. Complementarity Problems / Akiko Yoshise --
9. Semidefinite Programming / Motakuri V. Ramana and Panos M. Pardalos --
10. Implementing Barrier Methods for Nonlinear Programming / David F. Shanno, Mark G. Breitfeld and Evangelia M. Simantiraki --
11. Interior Point Methods for Combinatorial Optimization / John E. Mitchell.
Series Title: Applied optimization, v. 5.
Responsibility: edited by Tamás Terlaky.
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Abstract:

At the same time, we try to present a quick overview of the impact of extensions of IPMs on smooth nonlinear optimization and to demonstrate the potential of IPMs for solving difficult practical  Read more...

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