Handbook of Generalized Convexity and Generalized Monotonicity, Nicolas Hadjisavvas; S?ndor Koml?si; Siegfried S.

Автор: Nicolas Hadjisavvas; Juan E. Martinez-Legaz; Jean-
Название: Generalized Convexity and Generalized Monotonicity
ISBN: 3540418067 ISBN-13(EAN): 9783540418061
Издательство: Springer
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Описание: This volume contains a selection of refereed papers presented at the 6th International Symposium on Generalized Convexity/Monotonicity, and aims to review the latest developments in this interdisciplinary field.

Автор: Andrew Eberhard; Nicolas Hadjisavvas; D.T. Luc
Название: Generalized Convexity, Generalized Monotonicity and Applications
ISBN: 1441936475 ISBN-13(EAN): 9781441936479
Издательство: Springer
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Описание: In recent years there is a growing interest in generalized convex fu- tions and generalized monotone mappings among the researchers of - plied mathematics and other sciences.

Автор: Stephen Simons
Название: From Hahn-Banach to Monotonicity
ISBN: 1402069189 ISBN-13(EAN): 9781402069185
Издательство: Springer
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Описание: This new edition of LNM 1693 aims to reduce questions on monotone multifunctions to questions on convex functions. The journey begins with the Hahn-Banach theorem and culminates in a survey of current results on monotone multifunctions on a Banach space.

Автор: Shashi K. Mishra; Shouyang Wang; Kin Keung Lai
Название: Generalized Convexity and Vector Optimization
ISBN: 3642099300 ISBN-13(EAN): 9783642099304
Издательство: Springer
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Цена: 23058.00 р.
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Описание: This book discusses the Kuhn-Tucker Optimality, Karush-Kuhn-Tucker Necessary and Sufficient Optimality Conditions in presence of various types of generalized convexity assumptions. It details the present state of knowledge on research done in this area.

Автор: Alberto Cambini; Laura Martein
Название: Generalized Convexity and Optimization
ISBN: 3540708758 ISBN-13(EAN): 9783540708759
Издательство: Springer
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Цена: 14673.00 р.
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Описание: Offers a review of convex analysis and the fundamental theoretical findings on generalized convexity and on optimization, including their applications. This work includes a chapter devoted to generalized monotonicity and its relationship to generalized convexity and with the characterizations of important classes of fractional programming.

Автор: Luca Brandolini; Leonardo Colzani; Alex Iosevich;
Название: Fourier Analysis and Convexity
ISBN: 0817632638 ISBN-13(EAN): 9780817632632
Издательство: Springer
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Цена: 13974.00 р.
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Описание: in the past, study of this relationship has led to important mathematical advancesPresents new results and applications to diverse fields such as geometry, number theory, and analysisContributors are leading experts in their respective fieldsWill be of interest to both pure and applied mathematicians

Автор: Alexander M. Rubinov
Название: Abstract Convexity and Global Optimization
ISBN: 079236323X ISBN-13(EAN): 9780792363231
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Описание: Consisting of two parts, this work presents the main notions of abstract convexity and their applications in the study of some classes of functions and sets. It examines both theoretical and numerical aspects of global optimization based on abstract convexity. It is of interest to specialists in global optimization, and mathematical programming.

Автор: Karim Adiprasito; Imre B?r?ny; Costin Vilcu
Название: Convexity and Discrete Geometry Including Graph Theory
ISBN: 3319281844 ISBN-13(EAN): 9783319281841
Издательство: Springer
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Описание: This volume presents easy-to-understand yet surprising properties obtained using topological, geometric and graph theoretic tools in the areas covered by the Geometry Conference that took place in Mulhouse, France from September 7-11, 2014 in honour of Tudor Zamfirescu on the occasion of his 70th anniversary.

Автор: Viorel Barbu; Teodor Precupanu
Название: Convexity and Optimization in Banach Spaces
ISBN: 9401782415 ISBN-13(EAN): 9789401782418
Издательство: Springer
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Описание: In a revised edition, this book presents basic results of the theory of convex sets and functions in infinite-dimensional spaces. Includes new results on advanced concepts of subdifferential for convex functions and new duality results in convex programming.