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

By:

Peng, Jiming

Contributor(s):

Material type: Text

TextSeries: 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
9780691091921
0691091927

Subject(s): Genre/Form:

Electronic books.

Additional physical formats: Print version:: Self-regularity.DDC classification:

519.6 22

LOC classification:

QA402.5 .P4185 2002eb

Online resources:

Click here to access online

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.

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

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.