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Smooth Nonlinear Optimization of Rn - Rapcsák, Tamás
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Rapcsák, Tamás:
Smooth Nonlinear Optimization of Rn - hardcover

1997, ISBN: 0792346807, Lieferbar binnen 4-6 Wochen Shipping costs:Versandkostenfrei innerhalb der BRD

ID: 9780792346807

Internationaler Buchtitel. In englischer Sprache. Verlag: Springer-Verlag GmbH, HC runder Rücken kaschiert, 396 Seiten, L=235mm, B=155mm, H=26mm, Gew.=742gr, [GR: 16280 - HC/Mathematik/Wahrscheinlichkeitstheorie], [SW: - Differenzialgeometrie], Gebunden, Klappentext: This book is the first uniform, differential geometric approach to smooth nonlinear optimization. This advance allows the author to improve the sufficiency part of the Lagrange multiplier rule introduced in 1788 and to solve Fenchel's problem of level sets (1953) in the smooth case. Furthermore, this permits the author to replace convexity by geodesic convexity and apply it in complementarity systems, to study the nonlinear coordinate representations of smooth optimization problems, to describe the structure by tensors, to introduce a general framework for variable metric methods containing many basic nonlinear optimization algorithms, and - last but not least - to generate a class of polynomial interior point algorithms for linear optimization by a subclass of Riemannian metrics. Audience: The book is addressed to graduate students and researchers. The elementary notions necessary for understanding the material constitute part of the standard university curriculum. This book is the first uniform, differential geometric approach to smooth nonlinear optimization. This advance allows the author to improve the sufficiency part of the Lagrange multiplier rule introduced in 1788 and to solve Fenchel's problem of level sets (1953) in the smooth case. Furthermore, this permits the author to replace convexity by geodesic convexity and apply it in complementarity systems, to study the nonlinear coordinate representations of smooth optimization problems, to describe the structure by tensors, to introduce a general framework for variable metric methods containing many basic nonlinear optimization algorithms, and - last but not least - to generate a class of polynomial interior point algorithms for linear optimization by a subclass of Riemannian metrics. Audience: The book is addressed to graduate students and researchers. The elementary notions necessary for understanding the material constitute part of the standard university curriculum.

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Smooth Nonlinear Optimization of Rn - Rapcsák, Tamás
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(*)
Rapcsák, Tamás:
Smooth Nonlinear Optimization of Rn - hardcover

1997, ISBN: 0792346807, Lieferbar binnen 4-6 Wochen

ID: 9780792346807

Internationaler Buchtitel. In englischer Sprache. Verlag: Springer-Verlag GmbH, HC runder Rücken kaschiert, 396 Seiten, L=235mm, B=155mm, H=26mm, Gew.=742gr, [GR: 16280 - HC/Mathematik/Wahrscheinlichkeitstheorie], [SW: - Differenzialgeometrie], Gebunden, Klappentext: This book is the first uniform, differential geometric approach to smooth nonlinear optimization. This advance allows the author to improve the sufficiency part of the Lagrange multiplier rule introduced in 1788 and to solve Fenchel's problem of level sets (1953) in the smooth case. Furthermore, this permits the author to replace convexity by geodesic convexity and apply it in complementarity systems, to study the nonlinear coordinate representations of smooth optimization problems, to describe the structure by tensors, to introduce a general framework for variable metric methods containing many basic nonlinear optimization algorithms, and - last but not least - to generate a class of polynomial interior point algorithms for linear optimization by a subclass of Riemannian metrics. Audience: The book is addressed to graduate students and researchers. The elementary notions necessary for understanding the material constitute part of the standard university curriculum.

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Smooth Nonlinear Optimization of Rn - Rapcsák, Tamás
book is out-of-stock
(*)
Rapcsák, Tamás:
Smooth Nonlinear Optimization of Rn - hardcover

1997, ISBN: 0792346807, Lieferbar binnen 4-6 Wochen

ID: 9780792346807

Internationaler Buchtitel. In englischer Sprache. Verlag: Springer-Verlag GmbH, HC runder Rücken kaschiert, 396 Seiten, L=235mm, B=155mm, H=26mm, Gew.=742gr, [GR: 16280 - HC/Mathematik/Wahrscheinlichkeitstheorie], [SW: - Differenzialgeometrie], Gebunden, Klappentext: This book is the first uniform, differential geometric approach to smooth nonlinear optimization. This advance allows the author to improve the sufficiency part of the Lagrange multiplier rule introduced in 1788 and to solve Fenchel's problem of level sets (1953) in the smooth case. Furthermore, this permits the author to replace convexity by geodesic convexity and apply it in complementarity systems, to study the nonlinear coordinate representations of smooth optimization problems, to describe the structure by tensors, to introduce a general framework for variable metric methods containing many basic nonlinear optimization algorithms, and - last but not least - to generate a class of polynomial interior point algorithms for linear optimization by a subclass of Riemannian metrics. Audience: The book is addressed to graduate students and researchers. The elementary notions necessary for understanding the material constitute part of the standard university curriculum.

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Smooth Nonlinear Optimization of Rn - Rapcsák, Tamás
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1997, ISBN: 9780792346807

ID: 1865043&WAN=10022&WBT=28664&WMID=W000000443

1997. ; GEB ; Rapcsák:Smooth Nonlinear Optimization o This book is the first uniform, differential geometric approach to smooth nonlinear optimization. This advance allows the author to improve the sufficiency part of the Lagrange multiplier rule introduced in 1788 and to solve Fenchel's problem of level sets (1953) in the smooth case. Furthermore, this permits the author to replace convexity by geodesic convexity and apply it in complementarity systems, to study the nonlinear coordinate representations of smooth optimization problems, to describe the structure by tensors, to introduce a general framework for variable metric methods containing many basic nonlinear optimization algorithms, and - last but not least - to generate a class of polynomial interior point algorithms for linear optimization by a subclass of Riemannian metrics. Audience: The book is addressed to graduate students and researchers. The elementary notions necessary for understanding the material constitute part of the standard university curriculum. Buch gebund. Buch

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Smooth Nonlinear Optimization of RN - Tamas Rapcsak
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Tamas Rapcsak:
Smooth Nonlinear Optimization of RN - hardcover

1997, ISBN: 9780792346807

ID: 702995

Hardcover, Buch, [PU: Kluwer Academic Publishers]

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Details of the book
Smooth Nonlinear Optimization of Rn

This book is the first uniform, differential geometric approach to smooth nonlinear optimization. This advance allows the author to improve the sufficiency part of the Lagrange multiplier rule introduced in 1788 and to solve Fenchel's problem of level sets (1953) in the smooth case. Furthermore, this permits the author to replace convexity by geodesic convexity and apply it in complementarity systems, to study the nonlinear coordinate representations of smooth optimization problems, to describe the structure by tensors, to introduce a general framework for variable metric methods containing many basic nonlinear optimization algorithms, and - last but not least - to generate a class of polynomial interior point algorithms for linear optimization by a subclass of Riemannian metrics. Audience: The book is addressed to graduate students and researchers. The elementary notions necessary for understanding the material constitute part of the standard university curriculum.

Details of the book - Smooth Nonlinear Optimization of Rn


EAN (ISBN-13): 9780792346807
ISBN (ISBN-10): 0792346807
Hardcover
Publishing year: 1997
Publisher: Springer-Verlag GmbH
396 Pages
Weight: 0,742 kg
Language: eng/Englisch

Book in our database since 13.01.2008 17:19:34
Book found last time on 30.11.2016 01:06:16
ISBN/EAN: 9780792346807

ISBN - alternate spelling:
0-7923-4680-7, 978-0-7923-4680-7


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