Constructive Nonsmooth Analysis And Related Topics

The objective of the conference is to bring together mathematicians, physicists and engineers to present and discuss recent developments in the area of mathematical control methods, modelling and nonsmoth optimization The conference scope includes the following areas the design tools of nonsmooth analysis, nonsmooth problems of variational calculus and control theory, nonsmooth mechanics problem, nondifferentional optimization, nonsmooth analysis applications, mathematical modeling, mathematical problems of diagnostics, methods of game theory, nonlinear Chebyshev approximation and optimization

This volume contains a collection of papers based on lectures and presentations delivered at the International Conference on Constructive Nonsmooth Analysis (CNSA) held in St. Petersburg (Russia) from June 18-23, 2012. This conference was organized to mark the 50th anniversary of the birth of nonsmooth analysis and nondifferentiable optimization and was dedicated to J.-J. Moreau and the late B.N. Pshenichnyi, A.M. Rubinov, and N.Z. Shor, whose contributions to NSA and NDO remain invaluable. The first four chapters of the book are devoted to the theory of nonsmooth analysis. Chapters 5-8 contain new results in nonsmooth mechanics and calculus of variations. Chapters 9-13 are related to nondifferentiable optimization, and the volume concludes with four chapters containing interesting and important historical chapters, including tributes to three giants of nonsmooth analysis, convexity, and optimization: Alexandr Alexandrov, Leonid Kantorovich, and Alex Rubinov. The last chapter provides an overview and important snapshots of the 50-year history of convex analysis and optimization.

The subject of (static) optimization, also called mathematical programming, is one of the most important and widespread branches of modern mathematics, serving as a cornerstone of such scientific subjects as economic analysis, operations research, management sciences, engineering, chemistry, physics, statistics, computer science, biology, and social sciences. This book presents a unified, progressive treatment of the basic mathematical tools of mathematical programming theory. The authors expose said tools, along with results concerning the most common mathematical programming problems formulated in a finite-dimensional setting, forming the basis for further study of the basic questions on the various algorithmic methods and the most important particular applications of mathematical programming problems. This book assumes no previous experience in optimization theory, and the treatment of the various topics is largely self-contained. Prerequisites are the basic tools of differential calculus for functions of several variables, the basic notions of topology and of linear algebra, and the basic mathematical notions and theoretical background used in analyzing optimization problems. The book is aimed at both undergraduate and postgraduate students interested in mathematical programming problems but also those professionals who use optimization methods and wish to learn the more theoretical aspects of these questions.

Many practical problems can be described adequately only with the aid of nonsmooth functions. The book is mainly devoted to describing problems, tools and results in the area of Nonsmooth Analysis and Nondifferentiable Optimization, in particular those that can be easily transformed into practically applicable and computationally implementable ones. Most of the attention is paid to different generalizations of the concept of derivative (subdifferentials in Convex Analysis, the Clarke Subdifferential, Quasidifferentials, Codifferentials), Calculus of Quasidifferentials, Implicit Functions, Nonsmooth Extremal Problems.

This book presents tools and methods for large-scale and distributed optimization. Since many methods in "Big Data" fields rely on solving large-scale optimization problems, often in distributed fashion, this topic has over the last decade emerged to become very important. As well as specific coverage of this active research field, the book serves as a powerful source of information for practitioners as well as theoreticians. Large-Scale and Distributed Optimization is a unique combination of contributions from leading experts in the field, who were speakers at the LCCC Focus Period on Large-Scale and Distributed Optimization, held in Lund, 14th–16th June 2017. A source of information and innovative ideas for current and future research, this book will appeal to researchers, academics, and students who are interested in large-scale optimization.

2 Radiant sets 236 3 Co-radiant sets 239 4 Radiative and co-radiative sets 241 5 Radiant sets with Lipschitz continuous Minkowski gauges 245 6 Star-shaped sets and their kernels 249 7 Separation 251 8 Abstract convex star-shaped sets 255 References 260 11 DIFFERENCES OF CONVEX COMPACTA AND METRIC SPACES OF CON- 263 VEX COMPACTA WITH APPLICATIONS: A SURVEY A. M. Rubinov, A. A. Vladimirov 1 Introduction 264 2 Preliminaries 264 3 Differences of convex compact sets: general approach 266 4 Metric projections and corresponding differences (one-dimensional case) 267 5 The *-difference 269 6 The Demyanov difference 271 7 Geometric and inductive definitions of the D-difference 273 8 Applications to DC and quasidifferentiable functions 276 9 Differences of pairs of set-valued mappings with applications to quasidiff- entiability 278 10 Applications to approximate subdifferentials 280 11 Applications to the approximation of linear set-valued mappings 281 12 The Demyanov metric 282 13 The Bartels-Pallaschke metric 284 14 Hierarchy of the three norms on Qn 285 15 Derivatives 287 16 Distances from convex polyhedra and convergence of convex polyhedra 289 17 Normality of convex sets 290 18 D-regular sets 291 19 Variable D-regular sets 292 20 Optimization 293 References 294 12 CONVEX APPROXIMATORS.

This proceedings volume covers research in key areas of applied mathematical analysis, and gathers works presented at the international conference “Concord-90,” in honor of the 90th birthday of Professor Constantin Corduneanu (1928-2018). The event – which Professor Corduneanu was able to attend – was held at Ural Federal University in Ekaterinburg, Russia, on July 26-28, 2018. Professor Corduneanu’s research in mathematical analysis spanned nearly seven decades and explored a range of important issues in the field, including studies of global existence, stability problems, and oscillation theory, with special emphasis on various classes of nonlinear equations. He published over two hundred articles and several books, including “Almost Periodic Oscillations and Waves” (Springer, 2009). In this volume the reader will find selected, peer-reviewed articles from seven fields of research – Differential Equations, Optimal Control and Stabilization; Stochastic Methods; Topology and Functions Approximation; Mathematical Biology and Bioinformatics; Mathematical Modeling in Mining; Mathematical Modeling in Economics; and Computer Science and Image Processing – which honor and reflect Professor Corduneanu’s legacy in the fields of oscillation, stability and control theory.