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Fundamentals of Convex Analysis and Optimization
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, an...
Functional Analysis and Continuous Optimization
The book includes selected contributions presented at the "International Meeting on Functional Analysis and Continuous Optimization" held in Elche (Spain) on June 16–17, 2022. Its contents cover very recent results in functional analysis, continuous optimization and the interplay between these disciplines. Therefore, this book showcases current research on functional analysis and optimization with individual contributions, as well as new developments in both areas. As a result, the reader will find useful information and stimulating ideas.
Subdifferential Characterization of Probability Functions Under Gaussian Distribution
Probability functions figure prominently in optimization problems of engineering. They may be nonsmooth even if all input data are smooth. This fact motivates the consideration of subdifferentials for such typically just continuous functions. The aim of this paper is to provide subdifferential formulae of such functions in the case of Gaussian distributions for possibly infinite-dimensional decision variables and nonsmooth (locally Lipschitzian) input data. These formulae are based on the spheric-radial decomposition of Gaussian random vectors on the one hand and on a cone of directions of moderate growth on the other. By successively adding additional hypotheses, conditions are satisfied under which the probability function is locally Lipschitzian or even differentiable.
Convex Analysis and Beyond
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 m...
A Variational Approach to Nonsmooth Dynamics
This brief examines mathematical models in nonsmooth mechanics and nonregular electrical circuits, including evolution variational inequalities, complementarity systems, differential inclusions, second-order dynamics, Lur'e systems and Moreau's sweeping process. The field of nonsmooth dynamics is of great interest to mathematicians, mechanicians, automatic controllers and engineers. The present volume acknowledges this transversality and provides a multidisciplinary view as it outlines fundamental results in nonsmooth dynamics and explains how to use them to study various problems in engineering. In particular, the author explores the question of how to redefine the notion of dynamical systems in light of modern variational and nonsmooth analysis. With the aim of bridging between the communities of applied mathematicians, engineers and researchers in control theory and nonlinear systems, this brief outlines both relevant mathematical proofs and models in unilateral mechanics and electronics.
SEIO 2013 XXXIV Congreso nacional de estadística e investigación operativa. VII Jornadas de Estadística Pública. Libro de abstracts.
2013 ha sido designado Año Mundial de la Estadística y con los resultados del congreso, esta publicación contribuye al papel que el ISI quiere reforzar, que no es otro que la justa presencia y reconocimiento de la Estadística e Investigación Operativa en la sociedad. El libro se estructura de la siguiente forma: Conferencias plenarias (entre ellas la de Sixto Ros y Enrique Castillo); Candidatos al Premio Ramiro Melendreras; Contribuciones a los grupos SEIO; resto de contribuciones por categorías.
Contribution à la sensibilité et à la stabilité en optimisation et en théorie métrique des points critiques
Dans cette thèse nous proposons quelques contributions à l'analyse variationnelle dans les espaces métriques et à l'optimisation : régularité métrique, théorie métrique des points critiques, sensibilité de constantes de Hoffman, stabilité en programmation quadratique. Dans le cas polyédral nous établissons des formules explicites de constantes de Hoffman des polyèdres avec égalités explicites. Ensuite, en mettant en évidence le caractère lipschitzien de ces constantes, nous calculons le sous-différentiel de Clarke des fonctions associées. Nous faisons également une revue de la régularité métrique des multi-applications, et nous traitons la stabilité d'un problème quadratique convexe. La considération du concept de pente faible, et donc des techniques de déformation appropriées, nous permet d'établir des résultats de stabilité homotopique des points critiques isolés des fonctions continues.
Convex Analysis in General Vector Spaces
The primary aim of this book is to present the conjugate and sub/differential calculus using the method of perturbation functions in order to obtain the most general results in this field. The secondary aim is to provide important applications of this calculus and of the properties of convex functions. Such applications are: the study of well-conditioned convex functions, uniformly convex and uniformly smooth convex functions, best approximation problems, characterizations of convexity, the study of the sets of weak sharp minima, well-behaved functions and the existence of global error bounds for convex inequalities, as well as the study of monotone multifunctions by using convex functions.
Univariate Stable Distributions
This textbook highlights the many practical uses of stable distributions, exploring the theory, numerical algorithms, and statistical methods used to work with stable laws. Because of the author’s accessible and comprehensive approach, readers will be able to understand and use these methods. Both mathematicians and non-mathematicians will find this a valuable resource for more accurately modelling and predicting large values in a number of real-world scenarios. Beginning with an introductory chapter that explains key ideas about stable laws, readers will be prepared for the more advanced topics that appear later. The following chapters present the theory of stable distributions, a wide ra...
Nonlinear Optimization
This textbook on nonlinear optimization focuses on model building, real world problems, and applications of optimization models to natural and social sciences. Organized into two parts, this book may be used as a primary text for courses on convex optimization and non-convex optimization. Definitions, proofs, and numerical methods are well illustrated and all chapters contain compelling exercises. The exercises emphasize fundamental theoretical results on optimality and duality theorems, numerical methods with or without constraints, and derivative-free optimization. Selected solutions are given. Applications to theoretical results and numerical methods are highlighted to help students comprehend methods and techniques.
