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Smooth Nonlinear Optimization in Rn

Smooth Nonlinear Optimization in Rn

Nonconvex Optimization and Its Applications

by Tamas Rapcsak
Hardback
Publication Date: 31/08/1997

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This is a differential geometric approach to smooth nonlinear optimization. This 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.
ISBN:
9780792346807
9780792346807
Category:
Computer programming / software development
Format:
Hardback
Publication Date:
31-08-1997
Language:
English
Publisher:
Kluwer Academic Publishers
Country of origin:
United States
Pages:
376
Dimensions (mm):
234x156x22mm
Weight:
1.61kg

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