An Introduction To Interior Point Algorithms For Linear And Convex Quadratic Programming

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Interior Point Approach to Linear, Quadratic and Convex Programming

Author : D. den Hertog
Publisher : Springer Science & Business Media
ISBN 13 : 9401111340
Total Pages : 214 pages
Book Rating : 4.4/5 (11 download)

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Book Synopsis Interior Point Approach to Linear, Quadratic and Convex Programming by : D. den Hertog

Download or read book Interior Point Approach to Linear, Quadratic and Convex Programming written by D. den Hertog and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the rapidly developing field of interior point methods (IPMs). An extensive analysis is given of path-following methods for linear programming, quadratic programming and convex programming. These methods, which form a subclass of interior point methods, follow the central path, which is an analytic curve defined by the problem. Relatively simple and elegant proofs for polynomiality are given. The theory is illustrated using several explicit examples. Moreover, an overview of other classes of IPMs is given. It is shown that all these methods rely on the same notion as the path-following methods: all these methods use the central path implicitly or explicitly as a reference path to go to the optimum. For specialists in IPMs as well as those seeking an introduction to IPMs. The book is accessible to any mathematician with basic mathematical programming knowledge.

Interior-point Polynomial Algorithms in Convex Programming

Author : Yurii Nesterov
Publisher : SIAM
ISBN 13 : 9781611970791
Total Pages : 414 pages
Book Rating : 4.9/5 (77 download)

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Book Synopsis Interior-point Polynomial Algorithms in Convex Programming by : Yurii Nesterov

Download or read book Interior-point Polynomial Algorithms in Convex Programming written by Yurii Nesterov and published by SIAM. This book was released on 1994-01-01 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Specialists working in the areas of optimization, mathematical programming, or control theory will find this book invaluable for studying interior-point methods for linear and quadratic programming, polynomial-time methods for nonlinear convex programming, and efficient computational methods for control problems and variational inequalities. A background in linear algebra and mathematical programming is necessary to understand the book. The detailed proofs and lack of "numerical examples" might suggest that the book is of limited value to the reader interested in the practical aspects of convex optimization, but nothing could be further from the truth. An entire chapter is devoted to potential reduction methods precisely because of their great efficiency in practice.

An Introduction to Interior Point Algorithms for Linear and Convex Quadratic Programming

Author : B. Jansen
Publisher :
ISBN 13 :
Total Pages : 57 pages
Book Rating : 4.:/5 (662 download)

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Book Synopsis An Introduction to Interior Point Algorithms for Linear and Convex Quadratic Programming by : B. Jansen

Download or read book An Introduction to Interior Point Algorithms for Linear and Convex Quadratic Programming written by B. Jansen and published by . This book was released on 1992 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt:

A Unified Approach to Interior Point Algorithms for Linear Complementarity Problems

Author : Masakazu Kojima
Publisher : Springer Science & Business Media
ISBN 13 : 9783540545095
Total Pages : 124 pages
Book Rating : 4.5/5 (45 download)

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Book Synopsis A Unified Approach to Interior Point Algorithms for Linear Complementarity Problems by : Masakazu Kojima

Download or read book A Unified Approach to Interior Point Algorithms for Linear Complementarity Problems written by Masakazu Kojima and published by Springer Science & Business Media. This book was released on 1991-09-25 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: Following Karmarkar's 1984 linear programming algorithm, numerous interior-point algorithms have been proposed for various mathematical programming problems such as linear programming, convex quadratic programming and convex programming in general. This monograph presents a study of interior-point algorithms for the linear complementarity problem (LCP) which is known as a mathematical model for primal-dual pairs of linear programs and convex quadratic programs. A large family of potential reduction algorithms is presented in a unified way for the class of LCPs where the underlying matrix has nonnegative principal minors (P0-matrix). This class includes various important subclasses such as positive semi-definite matrices, P-matrices, P*-matrices introduced in this monograph, and column sufficient matrices. The family contains not only the usual potential reduction algorithms but also path following algorithms and a damped Newton method for the LCP. The main topics are global convergence, global linear convergence, and the polynomial-time convergence of potential reduction algorithms included in the family.

Interior Point Methods of Mathematical Programming

Author : Tamás Terlaky
Publisher : Springer Science & Business Media
ISBN 13 : 1461334497
Total Pages : 544 pages
Book Rating : 4.4/5 (613 download)

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Book Synopsis Interior Point Methods of Mathematical Programming by : Tamás Terlaky

Download or read book Interior Point Methods of Mathematical Programming written by Tamás Terlaky and published by Springer Science & Business Media. This book was released on 2013-12-01 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: One has to make everything as simple as possible but, never more simple. Albert Einstein Discovery consists of seeing what every body has seen and thinking what nobody has thought. Albert S. ent_Gyorgy; The primary goal of this book is to provide an introduction to the theory of Interior Point Methods (IPMs) in Mathematical Programming. At the same time, we try to present a quick overview of the impact of extensions of IPMs on smooth nonlinear optimization and to demonstrate the potential of IPMs for solving difficult practical problems. The Simplex Method has dominated the theory and practice of mathematical pro gramming since 1947 when Dantzig discovered it. In the fifties and sixties several attempts were made to develop alternative solution methods. At that time the prin cipal base of interior point methods was also developed, for example in the work of Frisch (1955), Caroll (1961), Huard (1967), Fiacco and McCormick (1968) and Dikin (1967). In 1972 Klee and Minty made explicit that in the worst case some variants of the simplex method may require an exponential amount of work to solve Linear Programming (LP) problems. This was at the time when complexity theory became a topic of great interest. People started to classify mathematical programming prob lems as efficiently (in polynomial time) solvable and as difficult (NP-hard) problems. For a while it remained open whether LP was solvable in polynomial time or not. The break-through resolution ofthis problem was obtained by Khachijan (1989).

Interior Point Algorithms

Author : Yinyu Ye
Publisher : John Wiley & Sons
ISBN 13 : 1118030958
Total Pages : 440 pages
Book Rating : 4.1/5 (18 download)

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Book Synopsis Interior Point Algorithms by : Yinyu Ye

Download or read book Interior Point Algorithms written by Yinyu Ye and published by John Wiley & Sons. This book was released on 2011-10-11 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first comprehensive review of the theory and practice of one oftoday's most powerful optimization techniques. The explosive growth of research into and development of interiorpoint algorithms over the past two decades has significantlyimproved the complexity of linear programming and yielded some oftoday's most sophisticated computing techniques. This book offers acomprehensive and thorough treatment of the theory, analysis, andimplementation of this powerful computational tool. Interior Point Algorithms provides detailed coverage of all basicand advanced aspects of the subject. Beginning with an overview offundamental mathematical procedures, Professor Yinyu Ye movesswiftly on to in-depth explorations of numerous computationalproblems and the algorithms that have been developed to solve them.An indispensable text/reference for students and researchers inapplied mathematics, computer science, operations research,management science, and engineering, Interior Point Algorithms: * Derives various complexity results for linear and convexprogramming * Emphasizes interior point geometry and potential theory * Covers state-of-the-art results for extension, implementation,and other cutting-edge computational techniques * Explores the hottest new research topics, including nonlinearprogramming and nonconvex optimization.

Primal-Dual Interior-Point Methods

Author : Stephen J. Wright
Publisher : SIAM
ISBN 13 : 089871382X
Total Pages : 293 pages
Book Rating : 4.8/5 (987 download)

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Book Synopsis Primal-Dual Interior-Point Methods by : Stephen J. Wright

Download or read book Primal-Dual Interior-Point Methods written by Stephen J. Wright and published by SIAM. This book was released on 1997-01-01 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents the major primal-dual algorithms for linear programming. A thorough, straightforward description of the theoretical properties of these methods.

A Simple, Quadratically Convergent Interior Point Algorithm for Linear Programming and Convex Quadratic Programming

Author : A. L. Tits
Publisher :
ISBN 13 :
Total Pages : 17 pages
Book Rating : 4.:/5 (897 download)

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Book Synopsis A Simple, Quadratically Convergent Interior Point Algorithm for Linear Programming and Convex Quadratic Programming by : A. L. Tits

Download or read book A Simple, Quadratically Convergent Interior Point Algorithm for Linear Programming and Convex Quadratic Programming written by A. L. Tits and published by . This book was released on 1993 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:

A Mathematical View of Interior-point Methods in Convex Optimization

Author : James Renegar
Publisher : SIAM
ISBN 13 : 9780898718812
Total Pages : 124 pages
Book Rating : 4.7/5 (188 download)

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Book Synopsis A Mathematical View of Interior-point Methods in Convex Optimization by : James Renegar

Download or read book A Mathematical View of Interior-point Methods in Convex Optimization written by James Renegar and published by SIAM. This book was released on 2001-01-01 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here is a book devoted to well-structured and thus efficiently solvable convex optimization problems, with emphasis on conic quadratic and semidefinite programming. The authors present the basic theory underlying these problems as well as their numerous applications in engineering, including synthesis of filters, Lyapunov stability analysis, and structural design. The authors also discuss the complexity issues and provide an overview of the basic theory of state-of-the-art polynomial time interior point methods for linear, conic quadratic, and semidefinite programming. The book's focus on well-structured convex problems in conic form allows for unified theoretical and algorithmical treatment of a wide spectrum of important optimization problems arising in applications.

Arc-Search Techniques for Interior-Point Methods

Author : Yaguang Yang
Publisher : CRC Press
ISBN 13 : 1000220133
Total Pages : 306 pages
Book Rating : 4.0/5 (2 download)

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Book Synopsis Arc-Search Techniques for Interior-Point Methods by : Yaguang Yang

Download or read book Arc-Search Techniques for Interior-Point Methods written by Yaguang Yang and published by CRC Press. This book was released on 2020-11-26 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses an important area of numerical optimization, called interior-point method. This topic has been popular since the 1980s when people gradually realized that all simplex algorithms were not convergent in polynomial time and many interior-point algorithms could be proved to converge in polynomial time. However, for a long time, there was a noticeable gap between theoretical polynomial bounds of the interior-point algorithms and efficiency of these algorithms. Strategies that were important to the computational efficiency became barriers in the proof of good polynomial bounds. The more the strategies were used in algorithms, the worse the polynomial bounds became. To further exacerbate the problem, Mehrotra's predictor-corrector (MPC) algorithm (the most popular and efficient interior-point algorithm until recently) uses all good strategies and fails to prove the convergence. Therefore, MPC does not have polynomiality, a critical issue with the simplex method. This book discusses recent developments that resolves the dilemma. It has three major parts. The first, including Chapters 1, 2, 3, and 4, presents some of the most important algorithms during the development of the interior-point method around the 1990s, most of them are widely known. The main purpose of this part is to explain the dilemma described above by analyzing these algorithms' polynomial bounds and summarizing the computational experience associated with them. The second part, including Chapters 5, 6, 7, and 8, describes how to solve the dilemma step-by-step using arc-search techniques. At the end of this part, a very efficient algorithm with the lowest polynomial bound is presented. The last part, including Chapters 9, 10, 11, and 12, extends arc-search techniques to some more general problems, such as convex quadratic programming, linear complementarity problem, and semi-definite programming.

Linear Programming

Author : Robert J Vanderbei
Publisher : Springer Science & Business Media
ISBN 13 : 1475756623
Total Pages : 451 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Linear Programming by : Robert J Vanderbei

Download or read book Linear Programming written by Robert J Vanderbei and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to optimization. It details constrained optimization, beginning with a substantial treatment of linear programming and proceeding to convex analysis, network flows, integer programming, quadratic programming, and convex optimization. Coverage underscores the purpose of optimization: to solve practical problems on a computer. C programs that implement the major algorithms and JAVA tools are available online.

Aspects of Semidefinite Programming

Author : E. de Klerk
Publisher : Springer Science & Business Media
ISBN 13 : 1402005474
Total Pages : 287 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Aspects of Semidefinite Programming by : E. de Klerk

Download or read book Aspects of Semidefinite Programming written by E. de Klerk and published by Springer Science & Business Media. This book was released on 2002-03-31 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: Semidefinite programming has been described as linear programming for the year 2000. It is an exciting new branch of mathematical programming, due to important applications in control theory, combinatorial optimization and other fields. Moreover, the successful interior point algorithms for linear programming can be extended to semidefinite programming. In this monograph the basic theory of interior point algorithms is explained. This includes the latest results on the properties of the central path as well as the analysis of the most important classes of algorithms. Several "classic" applications of semidefinite programming are also described in detail. These include the Lovász theta function and the MAX-CUT approximation algorithm by Goemans and Williamson. Audience: Researchers or graduate students in optimization or related fields, who wish to learn more about the theory and applications of semidefinite programming.

Interior Point Methods in Mathematical Programming

Author : Kurt M. Anstreicher
Publisher :
ISBN 13 :
Total Pages : 598 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Interior Point Methods in Mathematical Programming by : Kurt M. Anstreicher

Download or read book Interior Point Methods in Mathematical Programming written by Kurt M. Anstreicher and published by . This book was released on 1996 with total page 598 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Lectures on Modern Convex Optimization

Author : Aharon Ben-Tal
Publisher : SIAM
ISBN 13 : 0898714915
Total Pages : 500 pages
Book Rating : 4.8/5 (987 download)

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Book Synopsis Lectures on Modern Convex Optimization by : Aharon Ben-Tal

Download or read book Lectures on Modern Convex Optimization written by Aharon Ben-Tal and published by SIAM. This book was released on 2001-01-01 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here is a book devoted to well-structured and thus efficiently solvable convex optimization problems, with emphasis on conic quadratic and semidefinite programming. The authors present the basic theory underlying these problems as well as their numerous applications in engineering, including synthesis of filters, Lyapunov stability analysis, and structural design. The authors also discuss the complexity issues and provide an overview of the basic theory of state-of-the-art polynomial time interior point methods for linear, conic quadratic, and semidefinite programming. The book's focus on well-structured convex problems in conic form allows for unified theoretical and algorithmical treatment of a wide spectrum of important optimization problems arising in applications.

Interior Point Methods for Linear Optimization

Author : Cornelis Roos
Publisher : Springer Science & Business Media
ISBN 13 : 0387263799
Total Pages : 501 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Interior Point Methods for Linear Optimization by : Cornelis Roos

Download or read book Interior Point Methods for Linear Optimization written by Cornelis Roos and published by Springer Science & Business Media. This book was released on 2006-02-08 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: The era of interior point methods (IPMs) was initiated by N. Karmarkar’s 1984 paper, which triggered turbulent research and reshaped almost all areas of optimization theory and computational practice. This book offers comprehensive coverage of IPMs. It details the main results of more than a decade of IPM research. Numerous exercises are provided to aid in understanding the material.

A Study of Projective Algorithms for Linear and Convex Quadratic Programming

Author : Yufei Wang
Publisher :
ISBN 13 :
Total Pages : 244 pages
Book Rating : 4.E/5 ( download)

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Book Synopsis A Study of Projective Algorithms for Linear and Convex Quadratic Programming by : Yufei Wang

Download or read book A Study of Projective Algorithms for Linear and Convex Quadratic Programming written by Yufei Wang and published by . This book was released on 1992 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Aspects of Semidefinite Programming

Author : E. de Klerk
Publisher : Springer Science & Business Media
ISBN 13 : 0306478196
Total Pages : 287 pages
Book Rating : 4.3/5 (64 download)

DOWNLOAD NOW!

Book Synopsis Aspects of Semidefinite Programming by : E. de Klerk

Download or read book Aspects of Semidefinite Programming written by E. de Klerk and published by Springer Science & Business Media. This book was released on 2006-04-18 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: Semidefinite programming has been described as linear programming for the year 2000. It is an exciting new branch of mathematical programming, due to important applications in control theory, combinatorial optimization and other fields. Moreover, the successful interior point algorithms for linear programming can be extended to semidefinite programming. In this monograph the basic theory of interior point algorithms is explained. This includes the latest results on the properties of the central path as well as the analysis of the most important classes of algorithms. Several "classic" applications of semidefinite programming are also described in detail. These include the Lovász theta function and the MAX-CUT approximation algorithm by Goemans and Williamson. Audience: Researchers or graduate students in optimization or related fields, who wish to learn more about the theory and applications of semidefinite programming.