Mathematics Of Optimization Smooth And Nonsmooth Case

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Author: Giorgio Giorgi
Publisher: Elsevier
ISBN: 9780080535951
Size: 52.30 MB
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Mathematics Of Optimization Smooth And Nonsmooth Case by Giorgio Giorgi

Original Title: Mathematics Of Optimization Smooth And Nonsmooth Case

The book is intended for people (graduates, researchers, but also undergraduates with a good mathematical background) involved in the study of (static) optimization problems (in finite-dimensional spaces). It contains a lot of material, from basic tools of convex analysis to optimality conditions for smooth optimization problems, for non smooth optimization problems and for vector optimization problems. The development of the subjects are self-contained and the bibliographical references are usually treated in different books (only a few books on optimization theory deal also with vector problems), so the book can be a starting point for further readings in a more specialized literature. Assuming only a good (even if not advanced) knowledge of mathematical analysis and linear algebra, this book presents various aspects of the mathematical theory in optimization problems. The treatment is performed in finite-dimensional spaces and with no regard to algorithmic questions. After two chapters concerning, respectively, introductory subjects and basic tools and concepts of convex analysis, the book treats extensively mathematical programming problems in the smmoth case, in the nonsmooth case and finally vector optimization problems. · Self-contained · Clear style and results are either proved or stated precisely with adequate references · The authors have several years experience in this field · Several subjects (some of them non usual in books of this kind) in one single book, including nonsmooth optimization and vector optimization problems · Useful long references list at the end of each chapter

Invexity And Optimization

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Author: Shashi K. Mishra
Publisher: Springer Science & Business Media
ISBN: 3540785612
Size: 33.57 MB
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Invexity And Optimization by Shashi K. Mishra

Original Title: Invexity And Optimization

Invexity and Optimization presents results on invex function and their properties in smooth and nonsmooth cases, pseudolinearity and eta-pseudolinearity. Results on optimality and duality for a nonlinear scalar programming problem are presented, second and higher order duality results are given for a nonlinear scalar programming problem, and saddle point results are also presented. Invexity in multiobjective programming problems and Kuhn-Tucker optimality conditions are given for a multiobjecive programming problem, Wolfe and Mond-Weir type dual models are given for a multiobjective programming problem and usual duality results are presented in presence of invex functions. Continuous-time multiobjective problems are also discussed. Quadratic and fractional programming problems are given for invex functions. Symmetric duality results are also given for scalar and vector cases.

Constructive Nonsmooth Analysis And Related Topics

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Author: Vladimir F. Demyanov
Publisher: Springer Science & Business Media
ISBN: 1461486157
Size: 67.14 MB
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Constructive Nonsmooth Analysis And Related Topics by Vladimir F. Demyanov

Original Title: Constructive Nonsmooth Analysis And Related Topics

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.

Topics In Industrial Mathematics

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Author: H. Neunzert
Publisher: Springer Science & Business Media
ISBN: 9780792364177
Size: 27.54 MB
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Topics In Industrial Mathematics by H. Neunzert

Original Title: Topics In Industrial Mathematics

This book is devoted to some analytical and numerical methods for analyzing industrial problems related to emerging technologies such as digital image processing, material sciences and financial derivatives affecting banking and financial institutions. Case studies are based on industrial projects given by reputable industrial organizations of Europe to the Institute of Industrial and Business Mathematics, Kaiserslautern, Germany. Mathematical methods presented in the book which are most reliable for understanding current industrial problems include Iterative Optimization Algorithms, Galerkin's Method, Finite Element Method, Boundary Element Method, Quasi-Monte Carlo Method, Wavelet Analysis, and Fractal Analysis. The Black-Scholes model of Option Pricing, which was awarded the 1997 Nobel Prize in Economics, is presented in the book. In addition, basic concepts related to modeling are incorporated in the book. Audience: The book is appropriate for a course in Industrial Mathematics for upper-level undergraduate or beginning graduate-level students of mathematics or any branch of engineering.

Multilevel Optimization Algorithms And Applications

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Author: A. Migdalas
Publisher: Springer Science & Business Media
ISBN: 9780792346937
Size: 75.84 MB
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Multilevel Optimization Algorithms And Applications by A. Migdalas

Original Title: Multilevel Optimization Algorithms And Applications

In many decision processes there is an hierarchy of decision-makers and decisions are taken at different levels in this hierarchy. Multilevel programming focuses on the whole hierarchy structure. In terms of modeling, the constraint domain associated with a multilevel programming problem is implicitly determined by a series of optimization problems which must be solved in a predetermined sequence. The field of multilevel optimization has become a well-known and important research field. Hierarchical structures can be found in scientific disciplines such as environment, ecology, biology, chemical engineering, mechanics, classification theory, databases, network design, transportation, game theory and economics. Moreover, new applications are constantly being introduced. This has stimulated the development of new theory and efficient algorithms. This volume contains 16 chapters written by various leading researchers and presents a cohesive authoritative overview of developments and applications in their emerging field of optimization. Audience: Researchers whose work involves the application of mathematical programming and optimization to hierarchical structures.

Nonlinear Optimization And Applications

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Author: Gianni Pillo
Publisher: Springer Science & Business Media
ISBN: 1489902899
Size: 27.50 MB
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Nonlinear Optimization And Applications by Gianni Pillo

Original Title: Nonlinear Optimization And Applications

This volume contains the edited texts of the lectures presented at the workshop on Nonlinear Optimization: Theory and Applications, held in Erice at the "G. Stampacchia" School of Mathematics of the "E. Majorana" International Centre for Scientific Culture June 13-21, 1995. The meeting was conceived to review and discuss recent advances and promising research trends concerning theory, algorithms, and innovative applications in the field This is a field of mathematics which is providing viable of Nonlinear Optimization. tools in engineering, in economics and in other applied sciences, and which is giving a great contribution also in the solution of the more practiced linear optimization prob lems. The meeting was attended by approximately 70 people from 18 countries. Besides the lectures, several formal and informal discussions took place. The result was a broad exposure providing a wide and deep understanding of the present research achievements in the field. We wish to express our appreciation for the active contributions of all the partici pants in the meeting. Our gratitude is due to the Ettore Majorana Center in Erice, which offered its facilities and stimulating environment: its staff was certainly instrumental for the success of the meeting. Our gratitude is also due to Francisco Facchinei and Massino Roma for the time spent in the organization of the workshop, and to Giuliana Cai for the careful typesetting of this volume.

Applications Of Continuous Mathematics To Computer Science

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Author: Hung T. Nguyen
Publisher: Springer Science & Business Media
ISBN: 9780792347224
Size: 80.95 MB
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Applications Of Continuous Mathematics To Computer Science by Hung T. Nguyen

Original Title: Applications Of Continuous Mathematics To Computer Science

This volume is intended to be used as a textbook for a special topic course in computer science. It addresses contemporary research topics of interest such as intelligent control, genetic algorithms, neural networks, optimization techniques, expert systems, fractals, and computer vision. The work incorporates many new research ideas, and focuses on the role of continuous mathematics. Audience: This book will be valuable to graduate students interested in theoretical computer topics, algorithms, expert systems, neural networks, and software engineering.

Reformulation Nonsmooth Piecewise Smooth Semismooth And Smoothing Methods

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Author: Masao Fukushima
Publisher: Springer Science & Business Media
ISBN: 9780792353201
Size: 30.18 MB
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Reformulation Nonsmooth Piecewise Smooth Semismooth And Smoothing Methods by Masao Fukushima

Original Title: Reformulation Nonsmooth Piecewise Smooth Semismooth And Smoothing Methods

The concept of `reformulation' has long played an important role in mathematical programming. A classical example is the penalization technique in constrained optimization. More recent trends consist of reformulation of various mathematical programming problems, including variational inequalities and complementarity problems, into equivalent systems of possibly nonsmooth, piecewise smooth or semismooth nonlinear equations, or equivalent unconstrained optimization problems that are usually differentiable, but in general not twice differentiable. The book is a collection of peer-reviewed papers that cover such diverse areas as linear and nonlinear complementarity problems, variational inequality problems, nonsmooth equations and nonsmooth optimization problems, economic and network equilibrium problems, semidefinite programming problems, maximal monotone operator problems, and mathematical programs with equilibrium constraints. The reader will be convinced that the concept of `reformulation' provides extremely useful tools for advancing the study of mathematical programming from both theoretical and practical aspects. Audience: This book is intended for students and researchers in optimization, mathematical programming, and operations research.

Nonsmooth Optimization

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Author: Claude Lemarechal
Publisher: Elsevier
ISBN: 1483188760
Size: 46.85 MB
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Nonsmooth Optimization by Claude Lemarechal

Original Title: Nonsmooth Optimization

Nonsmooth Optimization contains the proceedings of a workshop on non-smooth optimization (NSO) held from March 28 to April 8,1977 in Austria under the auspices of the International Institute for Applied Systems Analysis. The papers explore the techniques and theory of NSO and cover topics ranging from systems of inequalities to smooth approximation of non-smooth functions, as well as quadratic programming and line searches. Comprised of nine chapters, this volume begins with a survey of Soviet research on subgradient optimization carried out since 1962, followed by a discussion on rates of convergence in subgradient optimization. The reader is then introduced to the method of subgradient optimization in an abstract setting and the minimal hypotheses required to ensure convergence; NSO and nonlinear programming; and bundle methods in NSO. A feasible descent algorithm for linearly constrained least squares problems is described. The book also considers sufficient minimization of piecewise-linear univariate functions before concluding with a description of the method of parametric decomposition in mathematical programming. This monograph will be of interest to mathematicians and mathematics students.

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