Amazon cover image
Image from Amazon.com

Self-regularity [electronic resource] : a new paradigm for primal-dual interior-point algorithms / Jiming Peng, Cornelis Roos, and Tamás Terlaky.

By: Contributor(s): Material type: TextTextSeries: Princeton series in applied mathematicsPublication details: Princeton, N.J. ; Oxford : Princeton University Press, ©2002.Description: 1 online resource (xiii, 185 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781400825134
  • 140082513X
  • 1400814529
  • 9781400814527
  • 9780691091938
  • 0691091935
Subject(s): Genre/Form: Additional physical formats: Print version:: Self-regularity.DDC classification:
  • 519.6 22
LOC classification:
  • QA402.5 .P4185 2002eb
Online resources:
Contents:
Preface; Acknowledgements; Notation; List of Abbreviations; Chapter 1. Introduction and Preliminaries; Chapter 2. Self-Regular Functions and Their Properties; Chapter 3. Primal-Dual Algorithms for Linear Optimization Based on Self-Regular Proximities; Chapter 4. Interior-Point Methods for Complementarity Problems Based on Self-Regular Proximities; Chapter 5. Primal-Dual Interior-Point Methods for Semidefinite Optimization Based on Self-Regular Proximities; Chapter 6. Primal-Dual Interior-Point Methods for Second-Order Conic Optimization Based on Self-Regular Proximities.
Summary: Research on interior-point methods (IPMs) has dominated the field of mathematical programming for the last two decades. Two contrasting approaches in the analysis and implementation of IPMs are the so-called small-update and large-update methods, although, until now, there has been a notorious gap between the theory and practical performance of these two strategies. This book comes close to bridging that gap, presenting a new framework for the theory of primal-dual IPMs based on the notion of the self-regularity of a function. The authors deal with linear optimization, nonlinear complementarity.
Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
eBook eBook e-Library EBSCO Mathematics Available
Total holds: 0

Includes bibliographical references (pages 175-181) and index.

Preface; Acknowledgements; Notation; List of Abbreviations; Chapter 1. Introduction and Preliminaries; Chapter 2. Self-Regular Functions and Their Properties; Chapter 3. Primal-Dual Algorithms for Linear Optimization Based on Self-Regular Proximities; Chapter 4. Interior-Point Methods for Complementarity Problems Based on Self-Regular Proximities; Chapter 5. Primal-Dual Interior-Point Methods for Semidefinite Optimization Based on Self-Regular Proximities; Chapter 6. Primal-Dual Interior-Point Methods for Second-Order Conic Optimization Based on Self-Regular Proximities.

Research on interior-point methods (IPMs) has dominated the field of mathematical programming for the last two decades. Two contrasting approaches in the analysis and implementation of IPMs are the so-called small-update and large-update methods, although, until now, there has been a notorious gap between the theory and practical performance of these two strategies. This book comes close to bridging that gap, presenting a new framework for the theory of primal-dual IPMs based on the notion of the self-regularity of a function. The authors deal with linear optimization, nonlinear complementarity.

Print version record.

Powered by Koha