Non-Convex Multi-Objective Optimization, Panos M. Pardalos; Antanas ?ilinskas; Julius ?ilin

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: 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: 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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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: D. Butnariu; A.N. Iusem
Название: Totally Convex Functions for Fixed Points Computation and Infinite Dimensional Optimization
ISBN: 9401057885 ISBN-13(EAN): 9789401057882
Издательство: Springer
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Описание: The aim of this work is to present in a unified approach a series of results concerning totally convex functions on Banach spaces and their applications to building iterative algorithms for computing common fixed points of mea- surable families of operators and optimization methods in infinite dimen- sional settings.

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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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: Sorin-Mihai Grad
Название: Vector Optimization and Monotone Operators via Convex Duality
ISBN: 3319088998 ISBN-13(EAN): 9783319088990
Издательство: Springer
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Цена: 15372.00 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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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: Sorin-Mihai Grad
Название: Vector Optimization and Monotone Operators via Convex Duality
ISBN: 3319361902 ISBN-13(EAN): 9783319361901
Издательство: Springer
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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: Juan Peypouquet
Название: Convex Optimization in Normed Spaces
ISBN: 3319137093 ISBN-13(EAN): 9783319137094
Издательство: Springer
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Описание: This work is intended to serve as a guide for graduate students and researchers who wish to get acquainted with the main theoretical and practical tools for the numerical minimization of convex functions on Hilbert spaces. Therefore, it contains the main tools that are necessary to conduct independent research on the topic.

Автор: Nesterov Y.
Название: Introductory Lectures on Convex Optimization / A Basic Course
ISBN: 1402075537 ISBN-13(EAN): 9781402075537
Издательство: Springer
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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.