Convex Analysis and Its Applications

Convex Analysis and Its Applications

In order to follow a similar pattern for quasiconvex duality, we are led to define in quasiconvex analysis the same analogous notions of conjugacy, biconjugacy and subgradient as we find in convex analysis. First of all, for a given ...

Author: A. Auslender

Publisher: Springer Science & Business Media

ISBN: 9783642482984

Category: Business & Economics

Page: 219

View: 513

Categories: Business & Economics

Convex Analysis

Convex Analysis

This book is an introduction to convex analysis and some of its applications.

Author: Georgii G. Magaril-Ilʹyaev

Publisher: American Mathematical Soc.

ISBN: 0821889648

Category: Mathematics

Page: 196

View: 406

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.
Categories: Mathematics

An Easy Path to Convex Analysis and Applications

An Easy Path to Convex Analysis and Applications

Chapter 4 is fullydevoted to applicationsofbasic results ofconvex analysis to problems of convex optimization and selected location problems considered from both qualitative and numerical viewpoints. Finally, we present at the end of ...

Author: Boris Mordukhovich

Publisher: Springer Nature

ISBN: 9783031024061

Category: Mathematics

Page: 202

View: 104

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 foundation for convex optimization, having deep knowledge of convex analysis helps students and researchers apply its tools more effectively. The main goal of this book is to provide an easy access to the most fundamental parts of convex analysis and its applications to optimization. Modern techniques of variational analysis are employed to clarify and simplify some basic proofs in convex analysis and build the theory of generalized differentiation for convex functions and sets in finite dimensions. We also present new applications of convex analysis to location problems in connection with many interesting geometric problems such as the Fermat-Torricelli problem, the Heron problem, the Sylvester problem, and their generalizations. Of course, we do not expect to touch every aspect of convex analysis, but the book consists of sufficient material for a first course on this subject. It can also serve as supplemental reading material for a course on convex optimization and applications.
Categories: Mathematics

Convex Analysis and Beyond

Convex Analysis and Beyond

this area and many excellent books have been published on various aspects of convex analysis and its applications in finite and infinite dimensions. Among them, we mention the books by Bauschke and Combettes [34], Bertsekas et al.

Author: Boris S. Mordukhovich

Publisher: Springer Nature

ISBN: 9783030947859

Category: Mathematics

Page: 585

View: 419

This book presents a unified theory of convex functions, sets, and set-valued mappings in topological vector spaces with its specifications to locally convex, Banach and finite-dimensional settings. These developments and expositions are based on the powerful geometric approach of variational analysis, which resides on set extremality with its characterizations and specifications in the presence of convexity. Using this approach, the text consolidates the device of fundamental facts of generalized differential calculus to obtain novel results for convex sets, functions, and set-valued mappings in finite and infinite dimensions. It also explores topics beyond convexity using the fundamental machinery of convex analysis to develop nonconvex generalized differentiation and its applications. The text utilizes an adaptable framework designed with researchers as well as multiple levels of students in mind. It includes many exercises and figures suited to graduate classes in mathematical sciences that are also accessible to advanced students in economics, engineering, and other applications. In addition, it includes chapters on convex analysis and optimization in finite-dimensional spaces that will be useful to upper undergraduate students, whereas the work as a whole provides an ample resource to mathematicians and applied scientists, particularly experts in convex and variational analysis, optimization, and their applications.
Categories: Mathematics

Convex Optimization

Convex Optimization

Convex analysis and optimization have an increasing impact on many areas of mathematics and applications ... (1993) and its abridged version (2002), Convex Analysis and Nonlinear Optimization by Borwein and Lewis (2000), Convex ...

Author: Mikhail Moklyachuk

Publisher: John Wiley & Sons

ISBN: 9781119804086

Category: Mathematics

Page: 272

View: 860

This book provides easy access to the basic principles and methods for solving constrained and unconstrained convex optimization problems. Included are sections that cover: basic methods for solving constrained and unconstrained optimization problems with differentiable objective functions; convex sets and their properties; convex functions and their properties and generalizations; and basic principles of sub-differential calculus and convex programming problems. Convex Optimization provides detailed proofs for most of the results presented in the book and also includes many figures and exercises for a better understanding of the material. Exercises are given at the end of each chapter, with solutions and hints to selected exercises given at the end of the book. Undergraduate and graduate students, researchers in different disciplines, as well as practitioners will all benefit from this accessible approach to convex optimization methods.
Categories: Mathematics

Convex Analysis for Optimization

Convex Analysis for Optimization

To avoid repetition, only proofs containing new ideas will be described in the book. Finally, in Chap. 9 some additional convex optimization applications are given. References Contents 1 Convex Sets: Basic Properties .

Author: Jan Brinkhuis

Publisher: Springer Nature

ISBN: 9783030418045

Category: Business & Economics

Page: 257

View: 270

This textbook offers graduate students a concise introduction to the classic notions of convex optimization. Written in a highly accessible style and including numerous examples and illustrations, it presents everything readers need to know about convexity and convex optimization. The book introduces a systematic three-step method for doing everything, which can be summarized as "conify, work, deconify". It starts with the concept of convex sets, their primal description, constructions, topological properties and dual description, and then moves on to convex functions and the fundamental principles of convex optimization and their use in the complete analysis of convex optimization problems by means of a systematic four-step method. Lastly, it includes chapters on alternative formulations of optimality conditions and on illustrations of their use. "The author deals with the delicate subjects in a precise yet light-minded spirit... For experts in the field, this book not only offers a unifying view, but also opens a door to new discoveries in convexity and optimization...perfectly suited for classroom teaching." Shuzhong Zhang, Professor of Industrial and Systems Engineering, University of Minnesota
Categories: Business & Economics

Conjugate Duality in Convex Optimization

Conjugate Duality in Convex Optimization

In: Agarwal RP, O'Regan D (eds) Nonlinear Analysis and Its Applications, Kluwer, Dordrecht, 807–822 Penot JP (2004): The relevance of convex analysis for the study of monotonicity. Nonlinear Analysis: Theory, Methods & Applications ...

Author: Radu Ioan Bot

Publisher: Springer Science & Business Media

ISBN: 9783642049002

Category: Business & Economics

Page: 164

View: 781

The results presented in this book originate from the last decade research work of the author in the ?eld of duality theory in convex optimization. The reputation of duality in the optimization theory comes mainly from the major role that it plays in formulating necessary and suf?cient optimality conditions and, consequently, in generatingdifferent algorithmic approachesfor solving mathematical programming problems. The investigations made in this work prove the importance of the duality theory beyond these aspects and emphasize its strong connections with different topics in convex analysis, nonlinear analysis, functional analysis and in the theory of monotone operators. The ?rst part of the book brings to the attention of the reader the perturbation approach as a fundamental tool for developing the so-called conjugate duality t- ory. The classical Lagrange and Fenchel duality approaches are particular instances of this general concept. More than that, the generalized interior point regularity conditions stated in the past for the two mentioned situations turn out to be p- ticularizations of the ones given in this general setting. In our investigations, the perturbationapproachrepresentsthestartingpointforderivingnewdualityconcepts for several classes of convex optimization problems. Moreover, via this approach, generalized Moreau–Rockafellar formulae are provided and, in connection with them, a new class of regularity conditions, called closedness-type conditions, for both stable strong duality and strong duality is introduced. By stable strong duality we understand the situation in which strong duality still holds whenever perturbing the objective function of the primal problem with a linear continuous functional.
Categories: Business & Economics

Convex Analysis and Nonlinear Optimization

Convex Analysis and Nonlinear Optimization

The powerful and elegant language of convex analysis unifies much of this theory. Hence our aim of writing a concise, accessible account of convex analysis and its applications and extensions, for a broad audience.

Author: Jonathan Borwein

Publisher: Springer Science & Business Media

ISBN: 9780387312569

Category: Mathematics

Page: 310

View: 633

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.
Categories: Mathematics

Convex Analysis and Optimization

Convex Analysis and Optimization

An important part of our approach has been to maintain a close link between the theoretical treatment of convexity and its application to optimization. For example, in Chapter 2, after the development of some of the basic facts about ...

Author: Dimitri Bertsekas

Publisher: Athena Scientific

ISBN: 9781886529458

Category: Mathematics

Page: 560

View: 696

A uniquely pedagogical, insightful, and rigorous treatment of the analytical/geometrical foundations of optimization. The book provides a comprehensive development of convexity theory, and its rich applications in optimization, including duality, minimax/saddle point theory, Lagrange multipliers, and Lagrangian relaxation/nondifferentiable optimization. It is an excellent supplement to several of our books: Convex Optimization Theory (Athena Scientific, 2009), Convex Optimization Algorithms (Athena Scientific, 2015), Nonlinear Programming (Athena Scientific, 2016), Network Optimization (Athena Scientific, 1998), and Introduction to Linear Optimization (Athena Scientific, 1997). Aside from a thorough account of convex analysis and optimization, the book aims to restructure the theory of the subject, by introducing several novel unifying lines of analysis, including: 1) A unified development of minimax theory and constrained optimization duality as special cases of duality between two simple geometrical problems. 2) A unified development of conditions for existence of solutions of convex optimization problems, conditions for the minimax equality to hold, and conditions for the absence of a duality gap in constrained optimization. 3) A unification of the major constraint qualifications allowing the use of Lagrange multipliers for nonconvex constrained optimization, using the notion of constraint pseudonormality and an enhanced form of the Fritz John necessary optimality conditions. Among its features the book: a) Develops rigorously and comprehensively the theory of convex sets and functions, in the classical tradition of Fenchel and Rockafellar b) Provides a geometric, highly visual treatment of convex and nonconvex optimization problems, including existence of solutions, optimality conditions, Lagrange multipliers, and duality c) Includes an insightful and comprehensive presentation of minimax theory and zero sum games, and its connection with duality d) Describes dual optimization, the associated computational methods, including the novel incremental subgradient methods, and applications in linear, quadratic, and integer programming e) Contains many examples, illustrations, and exercises with complete solutions (about 200 pages) posted at the publisher's web site http://www.athenasc.com/convexity.html
Categories: Mathematics