Overview
- Includes supplementary material: sn.pub/extras
Part of the book series: Nonconvex Optimization and Its Applications (NOIA, volume 89)
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Table of contents (12 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This up-to-date book is on algorithms for large-scale unconstrained and bound constrained optimization. Optimization techniques are shown from a conjugate gradient algorithm perspective.
Large part of the book is devoted to preconditioned conjugate gradient algorithms. In particular memoryless and limited memory quasi-Newton algorithms are presented and numerically compared to standard conjugate gradient algorithms.
The special attention is paid to the methods of shortest residuals developed by the author. Several effective optimization techniques based on these methods are presented.
Because of the emphasis on practical methods, as well as rigorous mathematical treatment of their convergence analysis, the book is aimed at a wide audience. It can be used by researches in optimization, graduate students in operations research, engineering, mathematics and computer science. Practitioners can benefit from numerous numerical comparisons of professional optimization codes discussed in the book.
Reviews
From the reviews:
"The book describes important algorithms for the numerical treatment of unconstrained nonlinear optimization problems with many variables. … This monograph is suitable as a text for a graduate course in computational optimization. It is useful to anyone active in this field. … This book is well written and well organized. The argument is clear. Lists of algorithms as well as tables and figures facilitate for the reader the search for desired information in the text. The reference list is comprehensive and contains 214 items." (Sven-Åke Gustafson, Mathematical Reviews, Issue 2009 i)
“It is a very nice written book which can be used by researchers in optimization, in the teaching for seminars and by students … . Lists of figures, tables and algorithms make this book to a useful compendium for research and teaching. A lot of bibliographical hints with respect to a large reference list make the reader known with the historical development of CG-methods … . appendices with elements of topology, analysis, linear algebra and numerics of linear algebra make it to a self-contained book.” (Armin Hoffmann, Zentralblatt MATH, Vol. 1171, 2009)
Authors and Affiliations
Bibliographic Information
Book Title: Conjugate Gradient Algorithms in Nonconvex Optimization
Authors: Radosław Pytlak
Series Title: Nonconvex Optimization and Its Applications
DOI: https://doi.org/10.1007/978-3-540-85634-4
Publisher: Springer Berlin, Heidelberg
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2009
Hardcover ISBN: 978-3-540-85633-7Published: 11 December 2008
Softcover ISBN: 978-3-642-09925-0Published: 20 November 2010
eBook ISBN: 978-3-540-85634-4Published: 18 November 2008
Series ISSN: 1571-568X
Edition Number: 1
Number of Pages: XXVI, 478
Topics: Calculus of Variations and Optimal Control; Optimization, Operations Research/Decision Theory, Quality Control, Reliability, Safety and Risk