Conjugate Gradient Algorithms in Nonconvex Optimization

Name: Conjugate Gradient Algorithms in Nonconvex Optimization
Brand: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
SKU: 9783540856337
Price: 3426 CZK
Availability: InStock

Autor: Radoslaw Pytlak

Jazyk:

Vazba: Pevná

Vydavatel: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Dostupnost: Skladem u dodavatele

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This up-to-date book is on algorithms for large-scale unconstrained and bound constrained optimizati...

Informace o knize

Autor

Radoslaw Pytlak

Jazyk

Angličtina

Vazba

Kniha - Pevná

Vydáno

2008

Stránek

478

EAN

9783540856337

ISBN

3540856331

Enbook ID

01570519

Vydavatel

Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Hmotnost

916

Rozměry

155 x 235 x 31

Kompletní popis

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.

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Conjugate Gradient Algorithms in Nonconvex Optimization

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