Vector Optimization and Monotone Operators via Convex Duality, Sorin-Mihai Grad

Автор: Stephen Boyd
Название: Convex Optimization
ISBN: 0521833787 ISBN-13(EAN): 9780521833783
Издательство: Cambridge Academ
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Описание: The focus of this book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance and economics.

Автор: Nesterov Y.
Название: Introductory Lectures on Convex Optimization / A Basic Course
ISBN: 1402075537 ISBN-13(EAN): 9781402075537
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This is the first elementary exposition of the main ideas of complexity theory for convex optimization. Up to now, most of the material can be found only in special journals and research monographs. The book covers optimal methods and lower complexity bounds for smooth and non-smooth convex optimization. A separate chapter is devoted to polynomial-time interior-point methods. Audience: The book is suitable for industrial engineers and economists.

Автор: Borwein, Jonathan M. Lewis, Adrian S. (university Of Waterloo)
Название: Convex analysis and nonlinear optimization
ISBN: 1441921273 ISBN-13(EAN): 9781441921277
Издательство: Springer
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Цена: 8378.00 р.
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Описание: Optimization is a rich and thriving mathematical discipline, and the underlying theory of current computational optimization techniques grows ever more sophisticated. This new edition adds material on semismooth optimization, as well as several new proofs.

Автор: Sorin-Mihai Grad
Название: Vector Optimization and Monotone Operators via Convex Duality
ISBN: 3319361902 ISBN-13(EAN): 9783319361901
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This book investigates several duality approaches for vector optimization problems, while also comparing them. Special attention is paid to duality for linear vector optimization problems, for which a vector dual that avoids the shortcomings of the classical ones is proposed.

Автор: Nicolas Hadjisavvas; Panos M. Pardalos
Название: Advances in Convex Analysis and Global Optimization
ISBN: 0792369424 ISBN-13(EAN): 9780792369424
Издательство: Springer
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Цена: 25155.00 р.
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Описание: A conference on Convex Analysis and Global Optimization was held in 2000 in Greece in honour of the memory of C. Caratheodory (1873-1950). This volume contains a selection of papers based on talks presented at the conference. The two themes of convexity and global optimization pervade the book.

Автор: Panos M. Pardalos; Antanas ?ilinskas; Julius ?ilin
Название: Non-Convex Multi-Objective Optimization
ISBN: 3319610058 ISBN-13(EAN): 9783319610054
Издательство: Springer
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Описание: Recent results on non-convex multi-objective optimization problems and methods are presented in this book, with particular attention to expensive black-box objective functions.

Автор: Roman G. Strongin; Yaroslav D. Sergeyev
Название: Global Optimization with Non-Convex Constraints
ISBN: 1461371171 ISBN-13(EAN): 9781461371175
Издательство: Springer
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Автор: Regina S. Burachik; Alfredo N. Iusem
Название: Set-Valued Mappings and Enlargements of Monotone Operators
ISBN: 1441943463 ISBN-13(EAN): 9781441943460
Издательство: Springer
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Цена: 9083.00 р.
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Описание: This is the first comprehensive book treatment of the emerging subdiscipline of set-valued mapping and enlargements of maximal monotone operators. Throughout the text, examples help readers make the bridge from theory to application. Numerous exercises are also offered to enable readers to apply and build their own skills and knowledge.

Автор: Roman G. Strongin; Yaroslav D. Sergeyev
Название: Global Optimization with Non-Convex Constraints
ISBN: 0792364902 ISBN-13(EAN): 9780792364900
Издательство: Springer
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Цена: 43184.00 р.
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Описание: Presents a new approach to global non-convex constrained optimization. Problem dimensionality is reduced via space-filling curves and to economize the search, constraint is accounted separately (penalties are not employed). The multicriteria case is also considered.

Автор: Alexander M. Rubinov; Xiao-qi Yang
Название: Lagrange-type Functions in Constrained Non-Convex Optimization
ISBN: 1461348218 ISBN-13(EAN): 9781461348214
Издательство: Springer
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Описание: Thus the question arises how to generalize classical Lagrange and penalty functions, in order to obtain an appropriate scheme for reducing constrained optimiza- tion problems to unconstrained ones that will be suitable for sufficiently broad classes of optimization problems from both the theoretical and computational viewpoints.

Автор: Radu Ioan Bot; Sorin-Mihai Grad; Gert Wanka
Название: Duality in Vector Optimization
ISBN: 3642269362 ISBN-13(EAN): 9783642269363
Издательство: Springer
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Описание: This book presents fundamentals and comprehensive results regarding duality for scalar, vector and set-valued optimization problems in a general setting. One chapter is exclusively consecrated to the scalar and vector Wolfe and Mond-Weir duality schemes.