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Author: Alexander M. Rubinov Publisher: Springer Science & Business Media ISBN: 1441991727 Category : Mathematics Languages : en Pages : 297
Book Description
Lagrange and penalty function methods provide a powerful approach, both as a theoretical tool and a computational vehicle, for the study of constrained optimization problems. However, for a nonconvex constrained optimization problem, the classical Lagrange primal-dual method may fail to find a mini mum as a zero duality gap is not always guaranteed. A large penalty parameter is, in general, required for classical quadratic penalty functions in order that minima of penalty problems are a good approximation to those of the original constrained optimization problems. It is well-known that penaity functions with too large parameters cause an obstacle for numerical implementation. Thus the question arises how to generalize classical Lagrange and penalty functions, in order to obtain an appropriate scheme for reducing constrained optimiza tion problems to unconstrained ones that will be suitable for sufficiently broad classes of optimization problems from both the theoretical and computational viewpoints. Some approaches for such a scheme are studied in this book. One of them is as follows: an unconstrained problem is constructed, where the objective function is a convolution of the objective and constraint functions of the original problem. While a linear convolution leads to a classical Lagrange function, different kinds of nonlinear convolutions lead to interesting generalizations. We shall call functions that appear as a convolution of the objective function and the constraint functions, Lagrange-type functions.
Author: Alexander M. Rubinov Publisher: Springer Science & Business Media ISBN: 1441991727 Category : Mathematics Languages : en Pages : 297
Book Description
Lagrange and penalty function methods provide a powerful approach, both as a theoretical tool and a computational vehicle, for the study of constrained optimization problems. However, for a nonconvex constrained optimization problem, the classical Lagrange primal-dual method may fail to find a mini mum as a zero duality gap is not always guaranteed. A large penalty parameter is, in general, required for classical quadratic penalty functions in order that minima of penalty problems are a good approximation to those of the original constrained optimization problems. It is well-known that penaity functions with too large parameters cause an obstacle for numerical implementation. Thus the question arises how to generalize classical Lagrange and penalty functions, in order to obtain an appropriate scheme for reducing constrained optimiza tion problems to unconstrained ones that will be suitable for sufficiently broad classes of optimization problems from both the theoretical and computational viewpoints. Some approaches for such a scheme are studied in this book. One of them is as follows: an unconstrained problem is constructed, where the objective function is a convolution of the objective and constraint functions of the original problem. While a linear convolution leads to a classical Lagrange function, different kinds of nonlinear convolutions lead to interesting generalizations. We shall call functions that appear as a convolution of the objective function and the constraint functions, Lagrange-type functions.
Author: Yichuang Sun Publisher: IET ISBN: 0863417450 Category : Technology & Engineering Languages : en Pages : 411
Book Description
This book provides a comprehensive discussion of automatic testing, diagnosis and tuning of analogue, mixed-signal and RF integrated circuits, and systems in a single source. As well as fundamental concepts and techniques, the book reports systematically the state of the arts and future research directions of those areas. A complete range of circuit components are covered and test issues from the SoC perspective. An essential reference for researchers and engineers in mixed signal testing, postgraduate and senior undergraduate students.
Author: Xiaoqi Yang Publisher: Springer Science & Business Media ISBN: 9780792362869 Category : Business & Economics Languages : en Pages : 376
Book Description
This is the second in a series of contributed, refereed volumes devoted to research in optimization by Australian researchers and their collaborators. These volumes are intended to have wide scope and include survey papers by established researchers providing up-to-date information on research directions. This volume includes survey and research papers on theories and methods of nonlinear programming, nonconvex and discrete optimization, stochastic linear programming, generalized convexity, complementarity and vector variational inequality problems, dynamic systems and optimal control and applications to traffic assignment models, train control, manufacturing systems and substrate diffusion of cutaneous tissue. Audience: Practitioners, postgraduate students and researchers in optimization.
Author: Xiao-qi Yang Publisher: Springer Science & Business Media ISBN: 146130301X Category : Mathematics Languages : en Pages : 347
Book Description
'Optimization Day' (OD) has been a series of annual mini-conferences in Aus tralia since 1994. The purpose of this series of events is to gather researchers in optimization and its related areas from Australia and their collaborators, in order to exchange new developments of optimization theories, methods and their applications. The first four OD mini-conferences were held in The Uni versity of Ballarat (1994), The University of New South Wales (1995), The University of Melbourne (1996) and Royal Melbourne Institute of Technology (1997), respectively. They were all on the eastern coast of Australia. The fifth mini-conference Optimization Days was held at the Centre for Ap plied Dynamics and Optimization (CADO), Department of Mathematics and Statistics, The University of Western Australia, Perth, from 29 to 30 June 1998. This is the first time the OD mini-conference has been held at the west ern coast of Australia. This fifth OD preceded the International Conference on Optimization: Techniques and Applications (ICOTA) held at Curtin Uni versity of Technology. Many participants attended both events. There were 28 participants in this year's mini-conference and 22 presentations in the mini conference. The presentations in this volume are refereed contributions based on papers presented at the fifth Optimization Days mini-conference. The volume is di vided into the following parts: Global Optimization, Nonsmooth Optimization, Optimization Methods and Applications.
Author: Alexander M. Rubinov Publisher: Springer Science & Business Media ISBN: 1475732007 Category : Mathematics Languages : en Pages : 506
Book Description
Special tools are required for examining and solving optimization problems. The main tools in the study of local optimization are classical calculus and its modern generalizions which form nonsmooth analysis. The gradient and various kinds of generalized derivatives allow us to ac complish a local approximation of a given function in a neighbourhood of a given point. This kind of approximation is very useful in the study of local extrema. However, local approximation alone cannot help to solve many problems of global optimization, so there is a clear need to develop special global tools for solving these problems. The simplest and most well-known area of global and simultaneously local optimization is convex programming. The fundamental tool in the study of convex optimization problems is the subgradient, which actu ally plays both a local and global role. First, a subgradient of a convex function f at a point x carries out a local approximation of f in a neigh bourhood of x. Second, the subgradient permits the construction of an affine function, which does not exceed f over the entire space and coincides with f at x. This affine function h is called a support func tion. Since f(y) ~ h(y) for ally, the second role is global. In contrast to a local approximation, the function h will be called a global affine support.
Author: Helmut E. Graeb Publisher: Springer Science & Business Media ISBN: 1402060041 Category : Technology & Engineering Languages : en Pages : 211
Book Description
What you’ll find here is a fascinating compendium of fundamental problem formulations of analog design centering and sizing. This essential work provides a differentiated knowledge about the tasks of analog design centering and sizing. In particular, worst-case scenarios are formulated and analyzed. This work is right at the crossing point between process and design technology, and is both reference work and textbook for understanding CAD methods in analog sizing.
Author: Thomas L., Saaty Publisher: RWS Publications ISBN: 1888603380 Category : Business & Economics Languages : en Pages : 404
Book Description
"We are surrounded and deeply involved, in the natural world, with non- linear events which are not necessarily mathematical," the authors write. "For example . . . the nonlinear problem of pedalling a bicycle up and down a hillside. On a grand scale . . . the struggle for existence between two species, one of which preys exclusively on the other." This book is' for mathematicians and researchers who believe that "nonlinear mathematics is' the mathematics of today"; it is also for economists, engineers, operations analysts, "the reader who has been thus bemused into an artificially linear conception of the universe." Nonlinear Mathematics is the first attempt to consider the widest range of nonlinear topics found in the -scattered literature. Accessible to non- mathematics professionals as well as college seniors and graduates, it offers a discussion both particular and broad enough to stimulate research towards a unifying theory of nonlinear mathematics. Ideas are presented "according to existence and uniqueness theorems, characterization (e.g., stability and asymptotic behavior), construction of solutions, convergence, approximation and errors."
Author: Richard W. Cottle Publisher: Springer ISBN: 1493970550 Category : Business & Economics Languages : en Pages : 644
Book Description
This textbook on Linear and Nonlinear Optimization is intended for graduate and advanced undergraduate students in operations research and related fields. It is both literate and mathematically strong, yet requires no prior course in optimization. As suggested by its title, the book is divided into two parts covering in their individual chapters LP Models and Applications; Linear Equations and Inequalities; The Simplex Algorithm; Simplex Algorithm Continued; Duality and the Dual Simplex Algorithm; Postoptimality Analyses; Computational Considerations; Nonlinear (NLP) Models and Applications; Unconstrained Optimization; Descent Methods; Optimality Conditions; Problems with Linear Constraints; Problems with Nonlinear Constraints; Interior-Point Methods; and an Appendix covering Mathematical Concepts. Each chapter ends with a set of exercises. The book is based on lecture notes the authors have used in numerous optimization courses the authors have taught at Stanford University. It emphasizes modeling and numerical algorithms for optimization with continuous (not integer) variables. The discussion presents the underlying theory without always focusing on formal mathematical proofs (which can be found in cited references). Another feature of this book is its inclusion of cultural and historical matters, most often appearing among the footnotes. "This book is a real gem. The authors do a masterful job of rigorously presenting all of the relevant theory clearly and concisely while managing to avoid unnecessary tedious mathematical details. This is an ideal book for teaching a one or two semester masters-level course in optimization – it broadly covers linear and nonlinear programming effectively balancing modeling, algorithmic theory, computation, implementation, illuminating historical facts, and numerous interesting examples and exercises. Due to the clarity of the exposition, this book also serves as a valuable reference for self-study." Professor Ilan Adler, IEOR Department, UC Berkeley "A carefully crafted introduction to the main elements and applications of mathematical optimization. This volume presents the essential concepts of linear and nonlinear programming in an accessible format filled with anecdotes, examples, and exercises that bring the topic to life. The authors plumb their decades of experience in optimization to provide an enriching layer of historical context. Suitable for advanced undergraduates and masters students in management science, operations research, and related fields." Michael P. Friedlander, IBM Professor of Computer Science, Professor of Mathematics, University of British Columbia
Author: Sabri Arik Publisher: Springer ISBN: 3319265555 Category : Computers Languages : en Pages : 725
Book Description
The four volume set LNCS 9489, LNCS 9490, LNCS 9491, and LNCS 9492 constitutes the proceedings of the 22nd International Conference on Neural Information Processing, ICONIP 2015, held in Istanbul, Turkey, in November 2015. The 231 full papers presented were carefully reviewed and selected from 375 submissions. The 4 volumes represent topical sections containing articles on Learning Algorithms and Classification Systems; Artificial Intelligence and Neural Networks: Theory, Design, and Applications; Image and Signal Processing; and Intelligent Social Networks.
Author: Alexander M. Rubinov
Author: Alexander M. Rubinov
Author: Yichuang Sun
Author: Xiaoqi Yang
Author: Xiao-qi Yang
Author: Alexander M. Rubinov
Author: Helmut E. Graeb
Author: A. F. Schwarz
Author: Thomas L., Saaty 
Author: Richard W. Cottle
Author: Sabri Arik