Convex Analysis and Global Optimization
Convex Analysis and Global Optimization

Author: Hoang Tuy

Publisher: Springer Science & Business Media

Published: 2013-03-09

Total Pages: 346

ISBN-13: 1475728093

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Due to the general complementary convex structure underlying most nonconvex optimization problems encountered in applications, convex analysis plays an essential role in the development of global optimization methods. This book develops a coherent and rigorous theory of deterministic global optimization from this point of view. Part I constitutes an introduction to convex analysis, with an emphasis on concepts, properties and results particularly needed for global optimization, including those pertaining to the complementary convex structure. Part II presents the foundation and application of global search principles such as partitioning and cutting, outer and inner approximation, and decomposition to general global optimization problems and to problems with a low-rank nonconvex structure as well as quadratic problems. Much new material is offered, aside from a rigorous mathematical development. Audience: The book is written as a text for graduate students in engineering, mathematics, operations research, computer science and other disciplines dealing with optimization theory. It is also addressed to all scientists in various fields who are interested in mathematical optimization.

Convex Functions and Their Applications
Convex Functions and Their Applications

Author: Constantin P. Niculescu

Publisher: Springer

Published: 2018-06-08

Total Pages: 430

ISBN-13: 3319783378

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Thorough introduction to an important area of mathematics Contains recent results Includes many exercises

Convex Analysis and Nonlinear Optimization
Convex Analysis and Nonlinear Optimization

Author: Jonathan Borwein

Publisher: Springer Science & Business Media

Published: 2010-05-05

Total Pages: 316

ISBN-13: 0387312560

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Optimization is a rich and thriving mathematical discipline, and the underlying theory of current computational optimization techniques grows ever more sophisticated. This book aims to provide a concise, accessible account of convex analysis and its applications and extensions, for a broad audience. Each section concludes with an often extensive set of optional exercises. This new edition adds material on semismooth optimization, as well as several new proofs.

Convex Analysis
Convex Analysis

Author: Georgii G. Magaril-Ilʹyaev

Publisher: American Mathematical Soc.

Published:

Total Pages: 196

ISBN-13: 9780821889640

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This book is an introduction to convex analysis and some of its applications. It starts with basis theory, which is explained within the framework of finite-dimensional spaces. The only prerequisites are basic analysis and simple geometry. The second chapter presents some applications of convex analysis, including problems of linear programming, geometry, and approximation. Special attention is paid to applications of convex analysis to Kolmogorov-type inequalities for derivatives of functions is one variable. Chapter 3 collects some results on geometry and convex analysis in infinite-dimensional spaces. A comprehensive introduction written "for beginners" illustrates the fundamentals of convex analysis in finite-dimensional spaces. The book can be used for an advanced undergraduate or graduate level course on convex analysis and its applications. It is also suitable for independent study of this extremely important area of mathematics.

Discrete Convex Analysis
Discrete Convex Analysis

Author: Kazuo Murota

Publisher: SIAM

Published: 2003-01-01

Total Pages: 411

ISBN-13: 9780898718508

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Discrete Convex Analysis is a novel paradigm for discrete optimization that combines the ideas in continuous optimization (convex analysis) and combinatorial optimization (matroid/submodular function theory) to establish a unified theoretical framework for nonlinear discrete optimization. The study of this theory is expanding with the development of efficient algorithms and applications to a number of diverse disciplines like matrix theory, operations research, and economics. This self-contained book is designed to provide a novel insight into optimization on discrete structures and should reveal unexpected links among different disciplines. It is the first and only English-language monograph on the theory and applications of discrete convex analysis.

Convex Analysis and Variational Problems
Convex Analysis and Variational Problems

Author: Ivar Ekeland

Publisher: SIAM

Published: 1999-12-01

Total Pages: 414

ISBN-13: 9781611971088

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This book contains different developments of infinite dimensional convex programming in the context of convex analysis, including duality, minmax and Lagrangians, and convexification of nonconvex optimization problems in the calculus of variations (infinite dimension). It also includes the theory of convex duality applied to partial differential equations; no other reference presents this in a systematic way. The minmax theorems contained in this book have many useful applications, in particular the robust control of partial differential equations in finite time horizon. First published in English in 1976, this SIAM Classics in Applied Mathematics edition contains the original text along with a new preface and some additional references.

Convex Analysis
Convex Analysis

Author: Steven G. Krantz

Publisher: CRC Press

Published: 2014-10-20

Total Pages: 174

ISBN-13: 149870638X

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Convexity is an ancient idea going back to Archimedes. Used sporadically in the mathematical literature over the centuries, today it is a flourishing area of research and a mathematical subject in its own right. Convexity is used in optimization theory, functional analysis, complex analysis, and other parts of mathematics.Convex Analysis introduces

Convex Functional Analysis
Convex Functional Analysis

Author: Andrew J. Kurdila

Publisher: Springer Science & Business Media

Published: 2006-03-30

Total Pages: 238

ISBN-13: 3764373571

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This volume is dedicated to the fundamentals of convex functional analysis. It presents those aspects of functional analysis that are extensively used in various applications to mechanics and control theory. The purpose of the text is essentially two-fold. On the one hand, a bare minimum of the theory required to understand the principles of functional, convex and set-valued analysis is presented. Numerous examples and diagrams provide as intuitive an explanation of the principles as possible. On the other hand, the volume is largely self-contained. Those with a background in graduate mathematics will find a concise summary of all main definitions and theorems.

An Easy Path to Convex Analysis and Applications
An Easy Path to Convex Analysis and Applications

Author: Boris S. Mordukhovich

Publisher: Morgan & Claypool Publishers

Published: 2013-12-01

Total Pages: 219

ISBN-13: 1627052380

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Convex optimization has an increasing impact on many areas of mathematics, applied sciences, and practical applications. It is now being taught at many universities and being used by researchers of different fields. As convex analysis is the mathematical f

Convex Sets and Their Applications
Convex Sets and Their Applications

Author: Steven R. Lay

Publisher: Courier Corporation

Published: 2007-01-01

Total Pages: 260

ISBN-13: 0486458032

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Suitable for advanced undergraduates and graduate students, this text introduces the broad scope of convexity. It leads students to open questions and unsolved problems, and it highlights diverse applications. Author Steven R. Lay, Professor of Mathematics at Lee University in Tennessee, reinforces his teachings with numerous examples, plus exercises with hints and answers. The first three chapters form the foundation for all that follows, starting with a review of the fundamentals of linear algebra and topology. They also survey the development and applications of relationships between hyperplanes and convex sets. Subsequent chapters are relatively self-contained, each focusing on a particular aspect or application of convex sets. Topics include characterizations of convex sets, polytopes, duality, optimization, and convex functions. Hints, solutions, and references for the exercises appear at the back of the book.