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Fundamentals of Convex Analysis and Optimization: A Supremum Function Approach

ISBN-13: 9783031295508 / Angielski

Rafael Correa; Abderrahim Hantoute; Marco A. López
Fundamentals of Convex Analysis and Optimization: A Supremum Function Approach Rafael Correa Abderrahim Hantoute Marco A. L?pez 9783031295508 Springer - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Fundamentals of Convex Analysis and Optimization: A Supremum Function Approach

ISBN-13: 9783031295508 / Angielski

Rafael Correa; Abderrahim Hantoute; Marco A. López
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This book aims at an innovative approach within the framework of convex analysis and optimization, based on an in-depth study of the behavior and properties of the supremum of families of convex functions. It presents an original and systematic treatment of convex analysis, covering standard results and improved calculus rules in subdifferential analysis. The tools supplied in the text allow a direct approach to the mathematical foundations of convex optimization, in particular to optimality and duality theory. Other applications in the book concern convexification processes in optimization, non-convex integration of the Fenchel subdifferential, variational characterizations of convexity, and the study of Chebychev sets. At the same time, the underlying geometrical meaning of all the involved concepts and operations is highlighted and duly emphasized. A notable feature of the book is its unifying methodology, as well as the novelty of providing an alternative or complementary view to the traditional one in which the discipline is presented to students and researchers.This textbook can be used for courses on optimization, convex and variational analysis, addressed to graduate and post-graduate students of mathematics, and also students of economics and engineering. It is also oriented to provide specific background for courses on optimal control, data science, operations research, economics (game theory), etc. The book represents a challenging and motivating development for those experts in functional analysis, convex geometry, and any kind of researchers who may be interested in applications of their work.

This book aims at an innovative approach within the framework of convex analysis and optimization, based on an in-depth study of the behavior and properties of the supremum of families of convex functions. It presents an original and systematic treatment of convex analysis, covering standard results and improved calculus rules in subdifferential analysis. The tools supplied in the text allow a direct approach to the mathematical foundations of convex optimization, in particular to optimality and duality theory. Other applications in the book concern convexification processes in optimization, non-convex integration of the Fenchel subdifferential, variational characterizations of convexity, and the study of Chebychev sets. At the same time, the underlying geometrical meaning of all the involved concepts and operations is highlighted and duly emphasized. A notable feature of the book is its unifying methodology, as well as the novelty of providing an alternative or complementary view to the traditional one in which the discipline is presented to students and researchers. 

This textbook can be used for courses on optimization, convex and variational analysis, addressed to graduate and post-graduate students of mathematics, and also students of economics and engineering. It is also oriented to provide specific background for courses on optimal control, data science, operations research, economics (game theory), etc. The book represents a challenging and motivating development for those experts in functional analysis, convex geometry, and any kind of researchers who may be interested in applications of their work.

Kategorie:
Nauka, Matematyka
Kategorie BISAC:
Business & Economics > Operations Research
Mathematics > Matematyka stosowana
Mathematics > Functional Analysis
Wydawca:
Springer
Seria wydawnicza:
Springer Operations Research and Financial Engineering
Język:
Angielski
ISBN-13:
9783031295508

1. Introduction

1.1 Motivation
1.2 Historical antecedents
1.3 Working framework and objectives

2. Preliminaries
2.1 Functional analysis background
2.2 Convexity and continuity
2.3 Examples of convex functions
2.4 Exercises
2.5 Bibliographical notes 

3. Fenchel-Moreau-Rockafellar theory
3.1 Conjugation theory
3.2 Fenchel-Moreau-Rockafellar theorem
3.3 Dual representations of support functions
3.4 Minimax theory
3.5 Exercises
3.6 Bibliographical notes

4. Fundamental topics in convex analysis
4.1 Subdifferential theory
4.2 Convex duality
4.3 Convexity in Banach spaces
4.4 Subdifferential integration
4.5 Exercises
4.6 Bibliographical notes

5. Supremum of convex functions
5.1 Conjugacy based approach
5.2 Main subdifferential formulas
 5.3 The role of continuity assumptions
5.4 Exercises
5.5 Bibliographical notes

 6. The supremum in specific contexts
6.1 The compact-continuous setting
6.2 Compactification approach
6.3 Main subdifferential formula revisited 
6.4 Homogeneous formulas
6.5 Qualification conditions 
6.6 Exercises
6.7 Bibliographical notes

7.  Other subdifferential calculus rules
7.1 Subdifferential of the sum
7.2 Symmetric versus asymmetric conditions
7.3 Supremum-sum subdifferential calculus 
7.4 Exercises
7.5 Bibliographical notes

8. Miscellaneous
8.1 Convex systems and Farkas-type qualifications
8.2 Optimality and duality in (semi)infinite convex optimization
8.3 Convexification processes in optimization
8.4 Non-convex integration
8.5 Variational characterization of convexity
8.6 Chebychev sets and convexity
8.7 Exercises
8.8 Bibliographical notes

 9. Exercises- Solutions
9.1 Exercises of chapter 2
9.2 Exercises of chapter 3
9.3 Exercises of chapter 4
9.4 Exercises of chapter 5
9.5 Exercises of chapter 6
9.6 Exercises of chapter 7
9.7 Exercises of chapter 8
 
Index
Glossary of Notations
Bibliography

Rafael Correa, Mathematical Engineering Degree from the University of Chile (1971), Doctor in Engineering, University of Clermont, France (1974) and Doctor in Mathematics Science, Blaise Pascal University, France (1984). He served as Executive Director of CONICYT, the Chilean National Agency for Scientific Research and Development (1990-1994), as Founder and Director of the Mathematical Modeling Center (CMM) at the University of Chile (2000-2007), and as President of O’Higgins University Chile, since its foundation in 2015. Author of fifty papers on Mathematical Optimization and Variational Analysis.


Abderrahim Hantoute, Doctor in Applied Mathematics from Université Paul Sabatier de Toulouse (2003), Postdoc Fellowship in Alicante and Elche Universities 2004-2007, Associate researcher (at CMM, Universidad de Chile until 2020, and then at Universidad de Alicante). According to MathSciNet: 47 papers, with 316 citations by 182 authors.

Marco A. López, Doctor in Mathematics from Valencia University (1973), Full Professor since 1981, currently at Alicante University as Emeritus Professor. Doctor Honoris Causa by the University of Limoges (2012), Honorary Adjunct Professor of Federation University, Australia (2013), as and Corresponding Member of the Real Academia de Ciencias of Spain (2014). Research on mathematical optimization, semi-infinite programming, variational analysis and game theory. According to MathSciNet: 151 papers, with 1788 citations by 590 authors.

This book aims at an innovative approach within the framework of convex analysis and optimization, based on an in-depth study of the behavior and properties of the supremum of families of convex functions. It presents an original and systematic treatment of convex analysis, covering standard results and improved calculus rules in subdifferential analysis. The tools supplied in the text allow a direct approach to the mathematical foundations of convex optimization, in particular to optimality and duality theory. Other applications in the book concern convexification processes in optimization, non-convex integration of the Fenchel subdifferential, variational characterizations of convexity, and the study of Chebychev sets. At the same time, the underlying geometrical meaning of all the involved concepts and operations is highlighted and duly emphasized. A notable feature of the book is its unifying methodology, as well as the novelty of providing an alternative or complementary view to the traditional one in which the discipline is presented to students and researchers. 

This textbook can be used for courses on optimization, convex and variational analysis, addressed to graduate and post-graduate students of mathematics, and also students of economics and engineering. It is also oriented to provide specific background for courses on optimal control, data science, operations research, economics (game theory), etc. The book represents a challenging and motivating development for those experts in functional analysis, convex geometry, and any kind of researchers who may be interested in applications of their work.





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