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Author : Krzysztof C. Kiwiel
Publisher : Springer
ISBN 13 : 3540395091
Total Pages : 369 pages
Book Rating : 4.5/5 (43 download)
Download or read book Methods of Descent for Nondifferentiable Optimization written by Krzysztof C. Kiwiel and published by Springer. This book was released on 2006-11-14 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Krzysztof C. Kiwiel
Publisher :
ISBN 13 : 9780387227191
Total Pages : 362 pages
Book Rating : 4.2/5 (271 download)
Download or read book Methods of descent for nondifferentiable optimization written by Krzysztof C. Kiwiel and published by . This book was released on 1985 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ulf Brännlund
Publisher :
ISBN 13 :
Total Pages : 14 pages
Book Rating : 4.:/5 (186 download)
Download or read book A Descent Proximal Level Bundle Method for Convex Nondifferentiable Optimization written by Ulf Brännlund and published by . This book was released on 1994 with total page 14 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ying Cui
Publisher : Society for Industrial and Applied Mathematics (SIAM)
ISBN 13 : 9781611976731
Total Pages : 0 pages
Book Rating : 4.9/5 (767 download)
Download or read book Modern Nonconvex Nondifferentiable Optimization written by Ying Cui and published by Society for Industrial and Applied Mathematics (SIAM). This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This monograph serves present and future needs where nonconvexity and nondifferentiability are inevitably present in the faithful modeling of real-world applications of optimization"--
Author : Vladimir Fedorovich Demʹi︠a︡nov
Publisher :
ISBN 13 :
Total Pages : 488 pages
Book Rating : 4.:/5 (327 download)
Download or read book Nondifferentiable Optimization written by Vladimir Fedorovich Demʹi︠a︡nov and published by . This book was released on 1985 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Michel Louis Balinski
Publisher :
ISBN 13 : 9780720483000
Total Pages : 0 pages
Book Rating : 4.4/5 (83 download)
Download or read book Nondifferentiable Optimization written by Michel Louis Balinski and published by . This book was released on 1975 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : N.Z. Shor
Publisher : Springer Science & Business Media
ISBN 13 : 1475760159
Total Pages : 407 pages
Book Rating : 4.4/5 (757 download)
Download or read book Nondifferentiable Optimization and Polynomial Problems written by N.Z. Shor and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: Polynomial extremal problems (PEP) constitute one of the most important subclasses of nonlinear programming models. Their distinctive feature is that an objective function and constraints can be expressed by polynomial functions in one or several variables. Let :e = {:e 1, ... , :en} be the vector in n-dimensional real linear space Rn; n PO(:e), PI (:e), ... , Pm (:e) are polynomial functions in R with real coefficients. In general, a PEP can be formulated in the following form: (0.1) find r = inf Po(:e) subject to constraints (0.2) Pi (:e) =0, i=l, ... ,m (a constraint in the form of inequality can be written in the form of equality by introducing a new variable: for example, P( x) ~ 0 is equivalent to P(:e) + y2 = 0). Boolean and mixed polynomial problems can be written in usual form by adding for each boolean variable z the equality: Z2 - Z = O. Let a = {al, ... ,a } be integer vector with nonnegative entries {a;}f=l. n Denote by R[a](:e) monomial in n variables of the form: n R[a](:e) = IT :ef'; ;=1 d(a) = 2:7=1 ai is the total degree of monomial R[a]. Each polynomial in n variables can be written as sum of monomials with nonzero coefficients: P(:e) = L caR[a](:e), aEA{P) IX x Nondifferentiable optimization and polynomial problems where A(P) is the set of monomials contained in polynomial P.
Author : Dimitri P. Bertsekas
Publisher :
ISBN 13 :
Total Pages : 6 pages
Book Rating : 4.:/5 (227 download)
Download or read book Steepest Descent for Optimization Problems with Nondifferentiable Cost Functionals written by Dimitri P. Bertsekas and published by . This book was released on 1971 with total page 6 pages. Available in PDF, EPUB and Kindle. Book excerpt: The steepest descent method is a commonly used algorithm for finding the minimum of a differentiable cost functional. At each iteration a descent is made at the direction of the negative gradient according to some step size selection scheme. This paper has two objectives. First to examine the natural extension of the steepest descent algorithm for minimizing a directionally differentiable function mapping R sup n into the real line. Second, the paper is to propose a new descent algorithm for minimizing an extended real valued convex function. (Author).
Author : Sergey Repin
Publisher : Springer Science & Business Media
ISBN 13 : 9400752881
Total Pages : 446 pages
Book Rating : 4.4/5 (7 download)
Download or read book Numerical Methods for Differential Equations, Optimization, and Technological Problems written by Sergey Repin and published by Springer Science & Business Media. This book was released on 2012-10-13 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the results in numerical analysis and optimization presented at the ECCOMAS thematic conference “Computational Analysis and Optimization” (CAO 2011) held in Jyväskylä, Finland, June 9–11, 2011. Both the conference and this volume are dedicated to Professor Pekka Neittaanmäki on the occasion of his sixtieth birthday. It consists of five parts that are closely related to his scientific activities and interests: Numerical Methods for Nonlinear Problems; Reliable Methods for Computer Simulation; Analysis of Noised and Uncertain Data; Optimization Methods; Mathematical Models Generated by Modern Technological Problems. The book also includes a short biography of Professor Neittaanmäki.
Author : Claude Lemarechal
Publisher : Elsevier
ISBN 13 : 1483188760
Total Pages : 195 pages
Book Rating : 4.4/5 (831 download)
Download or read book Nonsmooth Optimization written by Claude Lemarechal and published by Elsevier. This book was released on 2014-05-19 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : N.Z. Shor
Publisher : Springer Science & Business Media
ISBN 13 : 3642821189
Total Pages : 171 pages
Book Rating : 4.6/5 (428 download)
Download or read book Minimization Methods for Non-Differentiable Functions written by N.Z. Shor and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years much attention has been given to the development of auto matic systems of planning, design and control in various branches of the national economy. Quality of decisions is an issue which has come to the forefront, increasing the significance of optimization algorithms in math ematical software packages for al,ltomatic systems of various levels and pur poses. Methods for minimizing functions with discontinuous gradients are gaining in importance and the ~xperts in the computational methods of mathematical programming tend to agree that progress in the development of algorithms for minimizing nonsmooth functions is the key to the con struction of efficient techniques for solving large scale problems. This monograph summarizes to a certain extent fifteen years of the author's work on developing generalized gradient methods for nonsmooth minimization. This work started in the department of economic cybernetics of the Institute of Cybernetics of the Ukrainian Academy of Sciences under the supervision of V.S. Mikhalevich, a member of the Ukrainian Academy of Sciences, in connection with the need for solutions to important, practical problems of optimal planning and design. In Chap. I we describe basic classes of nonsmooth functions that are dif ferentiable almost everywhere, and analyze various ways of defining generalized gradient sets. In Chap. 2 we study in detail various versions of the su bgradient method, show their relation to the methods of Fejer-type approximations and briefly present the fundamentals of e-subgradient methods.
Author : V.F. Dem'yanov
Publisher : Springer
ISBN 13 : 9781461382683
Total Pages : 0 pages
Book Rating : 4.3/5 (826 download)
Download or read book Nondifferentiable Optimization written by V.F. Dem'yanov and published by Springer. This book was released on 2012-08-14 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Of recent coinage, the term "nondifferentiable optimization" (NDO) covers a spectrum of problems related to finding extremal values of nondifferentiable functions. Problems of minimizing nonsmooth functions arise in engineering applications as well as in mathematics proper. The Chebyshev approximation problem is an ample illustration of this. Without loss of generality, we shall consider only minimization problems. Among nonsmooth minimization problems, minimax problems and convex problems have been studied extensively ([31], [36], [57], [110], [120]). Interest in NDO has been constantly growing in recent years (monographs: [30], [81], [127] and articles and papers: [14], [20], [87]-[89], [98], [130], [135], [140]-[142], [152], [153], [160], all dealing with various aspects of non smooth optimization). For solving an arbitrary minimization problem, it is neces sary to: 1. Study properties of the objective function, in particular, its differentiability and directional differentiability. 2. Establish necessary (and, if possible, sufficient) condi tions for a global or local minimum. 3. Find the direction of descent (steepest or, simply, feasible--in appropriate sense). 4. Construct methods of successive approximation. In this book, the minimization problems for nonsmooth func tions of a finite number of variables are considered. Of fun damental importance are necessary conditions for an extremum (for example, [24], [45], [57], [73], [74], [103], [159], [163], [167], [168].
Author : Vladimir F. Demyanov
Publisher : Springer Science & Business Media
ISBN 13 : 3662126036
Total Pages : 355 pages
Book Rating : 4.6/5 (621 download)
Download or read book Nondifferentiable Optimization: Motivations and Applications written by Vladimir F. Demyanov and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: The International Institute for Applied Systems Analysis (IIASA) in Laxenburg, Austria, has been involved in research on nondifferentiable optimization since 1976. IIASA-based East-West cooperation in this field has been very productive, leading to many important theoretical, algorithmic and applied results. Nondifferentiable optimi zation has now become a recognized and rapidly developing branch of mathematical programming. To continue this tradition, and to review recent developments in this field, IIASA held a Workshop on Nondifferentiable Optimization in Sopron (Hungary) in September 1964. The aims of the Workshop were: 1. To discuss the state-of-the-art of nondifferentiable optimization (NDO), its origins and motivation; 2. To compare-various algorithms; 3. To evaluate existing mathematical approaches, their applications and potential; 4. To extend and deepen industrial and other applications of NDO. The following topics were considered in separate sessions: General motivation for research in NDO: nondifferentiability in applied problems, nondifferentiable mathematical models. Numerical methods for solving nondifferentiable optimization problems, numerical experiments, comparisons and software. Nondifferentiable analysis: various generalizations of the concept of subdifferen tials. Industrial and other applications. This volume contains selected papers presented at the Workshop. It is divided into four sections, based on the above topics: I. Concepts in Nonsmooth Analysis II. Multicriteria Optimization and Control Theory III. Algorithms and Optimization Methods IV. Stochastic Programming and Applications We would like to thank the International Institute for Applied Systems Analysis, particularly Prof. V. Kaftanov and Prof. A.B. Kurzhanski, for their support in organiz ing this meeting.
Author : Adil M. Bagirov
Publisher : Springer Nature
ISBN 13 : 3030349101
Total Pages : 696 pages
Book Rating : 4.0/5 (33 download)
Download or read book Numerical Nonsmooth Optimization written by Adil M. Bagirov and published by Springer Nature. This book was released on 2020-02-28 with total page 696 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solving nonsmooth optimization (NSO) problems is critical in many practical applications and real-world modeling systems. The aim of this book is to survey various numerical methods for solving NSO problems and to provide an overview of the latest developments in the field. Experts from around the world share their perspectives on specific aspects of numerical NSO. The book is divided into four parts, the first of which considers general methods including subgradient, bundle and gradient sampling methods. In turn, the second focuses on methods that exploit the problem’s special structure, e.g. algorithms for nonsmooth DC programming, VU decomposition techniques, and algorithms for minimax and piecewise differentiable problems. The third part considers methods for special problems like multiobjective and mixed integer NSO, and problems involving inexact data, while the last part highlights the latest advancements in derivative-free NSO. Given its scope, the book is ideal for students attending courses on numerical nonsmooth optimization, for lecturers who teach optimization courses, and for practitioners who apply nonsmooth optimization methods in engineering, artificial intelligence, machine learning, and business. Furthermore, it can serve as a reference text for experts dealing with nonsmooth optimization.
Author : Jorge Nocedal
Publisher : Springer Science & Business Media
ISBN 13 : 0387400656
Total Pages : 686 pages
Book Rating : 4.3/5 (874 download)
Download or read book Numerical Optimization written by Jorge Nocedal and published by Springer Science & Business Media. This book was released on 2006-12-11 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization is an important tool used in decision science and for the analysis of physical systems used in engineering. One can trace its roots to the Calculus of Variations and the work of Euler and Lagrange. This natural and reasonable approach to mathematical programming covers numerical methods for finite-dimensional optimization problems. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.
Author : J. Haslinger
Publisher : Springer Science & Business Media
ISBN 13 : 1475752334
Total Pages : 278 pages
Book Rating : 4.4/5 (757 download)
Download or read book Finite Element Method for Hemivariational Inequalities written by J. Haslinger and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hemivariational inequalities represent an important class of problems in nonsmooth and nonconvex mechanics. By means of them, problems with nonmonotone, possibly multivalued, constitutive laws can be formulated, mathematically analyzed and finally numerically solved. The present book gives a rigorous analysis of finite element approximation for a class of hemivariational inequalities of elliptic and parabolic type. Finite element models are described and their convergence properties are established. Discretized models are numerically treated as nonconvex and nonsmooth optimization problems. The book includes a comprehensive description of typical representants of nonsmooth optimization methods. Basic knowledge of finite element mathematics, functional and nonsmooth analysis is needed. The book is self-contained, and all necessary results from these disciplines are summarized in the introductory chapter. Audience: Engineers and applied mathematicians at universities and working in industry. Also graduate-level students in advanced nonlinear computational mechanics, mathematics of finite elements and approximation theory. Chapter 1 includes the necessary prerequisite materials.
Author : Marko M Makela
Publisher : World Scientific
ISBN 13 : 9814522414
Total Pages : 268 pages
Book Rating : 4.8/5 (145 download)
Download or read book Nonsmooth Optimization: Analysis And Algorithms With Applications To Optimal Control written by Marko M Makela and published by World Scientific. This book was released on 1992-05-07 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a self-contained elementary study for nonsmooth analysis and optimization, and their use in solution of nonsmooth optimal control problems. The first part of the book is concerned with nonsmooth differential calculus containing necessary tools for nonsmooth optimization. The second part is devoted to the methods of nonsmooth optimization and their development. A proximal bundle method for nonsmooth nonconvex optimization subject to nonsmooth constraints is constructed. In the last part nonsmooth optimization is applied to problems arising from optimal control of systems covered by partial differential equations. Several practical problems, like process control and optimal shape design problems are considered.
