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Conjugate Gradient Algorithms in Nonconvex Optimization

Name: Conjugate Gradient Algorithms in Nonconvex Optimization
Brand: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
SKU: 01570519
Price: 59544 HUF
Availability: InStock
Author: Radoslaw Pytlak
ISBN: 9783540856337

Radoslaw Pytlak

Language

English

Book Hardback

Libristo code: 01570519

Publishers Springer-Verlag Berlin and Heidelberg GmbH & Co. KG, November 2008

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

Libristo code: 01570519

406 b

59 544 Ft

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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.