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The Linearization Method For Constrained Optimization
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Book Synopsis The Linearization Method for Constrained Optimization by : Boris N. Pshenichnyj
Download or read book The Linearization Method for Constrained Optimization written by Boris N. Pshenichnyj and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: Techniques of optimization are applied in many problems in economics, automatic control, engineering, etc. and a wealth of literature is devoted to this subject. The first computer applications involved linear programming problems with simp- le structure and comparatively uncomplicated nonlinear pro- blems: These could be solved readily with the computational power of existing machines, more than 20 years ago. Problems of increasing size and nonlinear complexity made it necessa- ry to develop a complete new arsenal of methods for obtai- ning numerical results in a reasonable time. The lineariza- tion method is one of the fruits of this research of the last 20 years. It is closely related to Newton's method for solving systems of linear equations, to penalty function me- thods and to methods of nondifferentiable optimization. It requires the efficient solution of quadratic programming problems and this leads to a connection with conjugate gra- dient methods and variable metrics. This book, written by one of the leading specialists of optimization theory, sets out to provide - for a wide readership including engineers, economists and optimization specialists, from graduate student level on - a brief yet quite complete exposition of this most effective method of solution of optimization problems.
Book Synopsis Constrained Optimization and Lagrange Multiplier Methods by : Dimitri P. Bertsekas
Download or read book Constrained Optimization and Lagrange Multiplier Methods written by Dimitri P. Bertsekas and published by Academic Press. This book was released on 2014-05-10 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer Science and Applied Mathematics: Constrained Optimization and Lagrange Multiplier Methods focuses on the advancements in the applications of the Lagrange multiplier methods for constrained minimization. The publication first offers information on the method of multipliers for equality constrained problems and the method of multipliers for inequality constrained and nondifferentiable optimization problems. Discussions focus on approximation procedures for nondifferentiable and ill-conditioned optimization problems; asymptotically exact minimization in the methods of multipliers; duality framework for the method of multipliers; and the quadratic penalty function method. The text then examines exact penalty methods, including nondifferentiable exact penalty functions; linearization algorithms based on nondifferentiable exact penalty functions; differentiable exact penalty functions; and local and global convergence of Lagrangian methods. The book ponders on the nonquadratic penalty functions of convex programming. Topics include large scale separable integer programming problems and the exponential method of multipliers; classes of penalty functions and corresponding methods of multipliers; and convergence analysis of multiplier methods. The text is a valuable reference for mathematicians and researchers interested in the Lagrange multiplier methods.
Book Synopsis Linear and Nonlinear Optimization by : Richard W. Cottle
Download or read book Linear and Nonlinear Optimization written by Richard W. Cottle and published by Springer. This book was released on 2017-06-11 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Methods of Optimization by : Gordon Raymond Walsh
Download or read book Methods of Optimization written by Gordon Raymond Walsh and published by John Wiley & Sons. This book was released on 1975 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear programming; Search methods for unconstrained optimization; Gradient methods for unconstrained optimziation; Constrained optimization; Dynamic programming.
Book Synopsis Non-linear Optimization Techniques by : M. J. Box
Download or read book Non-linear Optimization Techniques written by M. J. Box and published by Oliver & Boyd. This book was released on 1969 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Numerical Methods for Constrained Optimization by : Philip E. Gill
Download or read book Numerical Methods for Constrained Optimization written by Philip E. Gill and published by . This book was released on 1974 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Reformulation-Linearization Technique for Solving Discrete and Continuous Nonconvex Problems by : Hanif D. Sherali
Download or read book A Reformulation-Linearization Technique for Solving Discrete and Continuous Nonconvex Problems written by Hanif D. Sherali and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 529 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with the theory and applications of the Reformulation- Linearization/Convexification Technique (RL T) for solving nonconvex optimization problems. A unified treatment of discrete and continuous nonconvex programming problems is presented using this approach. In essence, the bridge between these two types of nonconvexities is made via a polynomial representation of discrete constraints. For example, the binariness on a 0-1 variable x . can be equivalently J expressed as the polynomial constraint x . (1-x . ) = 0. The motivation for this book is J J the role of tight linear/convex programming representations or relaxations in solving such discrete and continuous nonconvex programming problems. The principal thrust is to commence with a model that affords a useful representation and structure, and then to further strengthen this representation through automatic reformulation and constraint generation techniques. As mentioned above, the focal point of this book is the development and application of RL T for use as an automatic reformulation procedure, and also, to generate strong valid inequalities. The RLT operates in two phases. In the Reformulation Phase, certain types of additional implied polynomial constraints, that include the aforementioned constraints in the case of binary variables, are appended to the problem. The resulting problem is subsequently linearized, except that certain convex constraints are sometimes retained in XV particular special cases, in the Linearization/Convexijication Phase. This is done via the definition of suitable new variables to replace each distinct variable-product term. The higher dimensional representation yields a linear (or convex) programming relaxation.
Book Synopsis Numerical Methods for Constrained and Unconstrained Optimization by : Paul T. Boggs
Download or read book Numerical Methods for Constrained and Unconstrained Optimization written by Paul T. Boggs and published by . This book was released on 1982 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main thrust of the research has been toward the development of efficient algorithms for solving the finite - dimensional constrained optimization problem. Historically, problems of this type have been solved by either penalty function methods or through linearization procedures. The fact that neither of these techniques is completely satisfactory for general nonlinear problems has lead to a concentrated research effort to find better approaches. What has so far emerged from this work is a blending of the penalty function land linearization ideas with the quadratic approximation methods associated with unconstrained optimization. While there remain many unresolved issues, it is now apparent that this synthesis has resulted in more efficient algorithms for the nonlinear constrained optimization problem. (Author).
Book Synopsis Practical Augmented Lagrangian Methods for Constrained Optimization by : Ernesto G. Birgin
Download or read book Practical Augmented Lagrangian Methods for Constrained Optimization written by Ernesto G. Birgin and published by SIAM. This book was released on 2014-04-30 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on Augmented Lagrangian techniques for solving practical constrained optimization problems. The authors: rigorously delineate mathematical convergence theory based on sequential optimality conditions and novel constraint qualifications; orient the book to practitioners by giving priority to results that provide insight on the practical behavior of algorithms and by providing geometrical and algorithmic interpretations of every mathematical result; and fully describe a freely available computational package for constrained optimization and illustrate its usefulness with applications.
Book Synopsis Practical Methods of Optimization: Constrained optimization by : Roger Fletcher
Download or read book Practical Methods of Optimization: Constrained optimization written by Roger Fletcher and published by . This book was released on 1980 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimization Under Constraints by : Peter Whittle
Download or read book Optimization Under Constraints written by Peter Whittle and published by John Wiley & Sons. This book was released on 1971 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: First thoughts on maximization; Constrained maximization and lagrangian methods; The strong lagrangian principle: convexity; Linear programming; Some particular linear problems; Some problems with linear constraints; Nonlinear constraints, and stochastic effects; Numerical methods; Vector maximization problems.
Book Synopsis Iterative Methods for Optimization by : C. T. Kelley
Download or read book Iterative Methods for Optimization written by C. T. Kelley and published by SIAM. This book was released on 1999-01-01 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a carefully selected group of methods for unconstrained and bound constrained optimization problems and analyzes them in depth both theoretically and algorithmically. It focuses on clarity in algorithmic description and analysis rather than generality, and while it provides pointers to the literature for the most general theoretical results and robust software, the author thinks it is more important that readers have a complete understanding of special cases that convey essential ideas. A companion to Kelley's book, Iterative Methods for Linear and Nonlinear Equations (SIAM, 1995), this book contains many exercises and examples and can be used as a text, a tutorial for self-study, or a reference. Iterative Methods for Optimization does more than cover traditional gradient-based optimization: it is the first book to treat sampling methods, including the Hooke-Jeeves, implicit filtering, MDS, and Nelder-Mead schemes in a unified way, and also the first book to make connections between sampling methods and the traditional gradient-methods. Each of the main algorithms in the text is described in pseudocode, and a collection of MATLAB codes is available. Thus, readers can experiment with the algorithms in an easy way as well as implement them in other languages.
Book Synopsis Preconditioning Methods for Linear Systems Arising in Constrained Optimization Problems by : A. Owe H. Axelsson
Download or read book Preconditioning Methods for Linear Systems Arising in Constrained Optimization Problems written by A. Owe H. Axelsson and published by . This book was released on 2002 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Linear Optimization by : Glenn Hurlbert
Download or read book Linear Optimization written by Glenn Hurlbert and published by Springer Science & Business Media. This book was released on 2009-11-09 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Subject A little explanation is in order for our choice of the title Linear Opti- 1 mization (and corresponding terminology) for what has traditionally been called Linear Programming.Theword programming in this context can be confusing and/or misleading to students. Linear programming problems are referred to as optimization problems but the general term linear p- gramming remains. This can cause people unfamiliar with the subject to think that it is about programming in the sense of writing computer code. It isn’t. This workbook is about the beautiful mathematics underlying the ideas of optimizing linear functions subject to linear constraints and the algorithms to solve such problems. In particular, much of what we d- cuss is the mathematics of Simplex Algorithm for solving such problems, developed by George Dantzig in the late 1940s. The word program in linear programming is a historical artifact. When Dantzig ?rstdevelopedthe Simplex Algorithm to solvewhat arenowcalled linear programming problems, his initial model was a class of resource - location problems to be solved for the U.S. Air Force. The decisions about theallocationswerecalled‘Programs’bytheAirForce,andhencetheterm.
Book Synopsis Practical Methods of Optimization by : R. Fletcher
Download or read book Practical Methods of Optimization written by R. Fletcher and published by John Wiley & Sons. This book was released on 2013-06-06 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fully describes optimization methods that are currently most valuable in solving real-life problems. Since optimization has applications in almost every branch of science and technology, the text emphasizes their practical aspects in conjunction with the heuristics useful in making them perform more reliably and efficiently. To this end, it presents comparative numerical studies to give readers a feel for possibile applications and to illustrate the problems in assessing evidence. Also provides theoretical background which provides insights into how methods are derived. This edition offers revised coverage of basic theory and standard techniques, with updated discussions of line search methods, Newton and quasi-Newton methods, and conjugate direction methods, as well as a comprehensive treatment of restricted step or trust region methods not commonly found in the literature. Also includes recent developments in hybrid methods for nonlinear least squares; an extended discussion of linear programming, with new methods for stable updating of LU factors; and a completely new section on network programming. Chapters include computer subroutines, worked examples, and study questions.
Book Synopsis Engineering Optimization by : Singiresu S. Rao
Download or read book Engineering Optimization written by Singiresu S. Rao and published by John Wiley & Sons. This book was released on 1996-02-29 with total page 926 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Engineering Optimization, Professor Singiresu S. Rao provides an application-oriented presentation of the full array of classical and newly developed optimization techniques now being used by engineers in a wide range of industries.
Book Synopsis Preconditioning Methods for Constrained Optimization Problems with Applications for the Linear Elasticity Equations by : A. Owe H. Axelsson
Download or read book Preconditioning Methods for Constrained Optimization Problems with Applications for the Linear Elasticity Equations written by A. Owe H. Axelsson and published by . This book was released on 2003 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt:
