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Book Linear Programming Algorithms Using Least squares Method

Download or read book Linear Programming Algorithms Using Least squares Method written by Seunghyun Kong and published by . This book was released on 2007 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our computational results show that the least-squares primal-dual algorithm and the combined-objective least-squares algorithm perform better than the CPLEX Primal solver, but are slower than the CPLEX Dual solver. The least-squares network flow algorithm performs as fast as the CPLEX Network solver.

Book A Strictly Improving Linear Programming Algorithm Using Least squares Subproblems

Download or read book A Strictly Improving Linear Programming Algorithm Using Least squares Subproblems written by Stephanie A. Leichner and published by . This book was released on 1991 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Linear Least Squares Computations

Download or read book Linear Least Squares Computations written by Farebrother and published by Routledge. This book was released on 2018-05-02 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting numerous algorithms in a simple algebraic form so that the reader can easilytranslate them into any computer language, this volume gives details of several methodsfor obtaining accurate least squares estimates. It explains how these estimates may beupdated as new information becomes available and how to test linear hypotheses.Linear Least Squares Computations features many structured exercises that guidethe reader through the available algorithms, plus a glossary of commonly used terms anda bibliography of supplementary reading ... collects "ancient" and modem results onlinear least squares computations in a convenient single source . . . develops the necessarymatrix algebra in the context of multivariate statistics . .. only makes peripheral use ofconcepts such as eigenvalues and partial differentiation .. . interprets canonical formsemployed in computation ... discusses many variants of the Gauss, Laplace-Schmidt,Givens, and Householder algorithms ... and uses an empirical approach for the appraisalof algorithms.Linear Least Squares Computations serves as an outstanding reference forindustrial and applied mathematicians, statisticians, and econometricians, as well as atext for advanced undergraduate and graduate statistics, mathematics, and econometricscourses in computer programming, linear regression analysis, and applied statistics.

Book Least Squares Methods for Linear Programming Problems

Download or read book Least Squares Methods for Linear Programming Problems written by Balaji Gopalakrishnan and published by LAP Lambert Academic Publishing. This book was released on 2011-06 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear programming has evolved over the years, due tosustained research and testing, as an excellent mathematical tool for solving manytheoretical and practical problems.Yet, escalating problem sizes in practical problemspose serious challenges for the verybest linear programming codes, running on the fastestcomputing hardware. New linearprogramming solution techniques have to developed tomeet these challenges. Theresearch performed in this book intends to addressthis issue through a comprehensivestudy of least-squares methods for solving linearprogramming problems.We have developed two new linear programmingalgorithms based on least-squarestheory. A Combined Objectives Least-Squares (COLS)algorithm uses a Non-NegativeLeast-Squares (NNLS) algorithm framework for solvingboth the Phase I and Phase IIlinear programming problems. A Least-SquaresPrimal-Dual (LSPD) algorithm usesNNLS solutions by solving small NNLS problems tosolve relatively larger linear programmingproblems. These algorithms are impervious todegeneracy. Computationalresults for the algorithms shows a superiorperformance over the simplex algorithmon a wide range of linear programming problems

Book A Strictly Improving Linear Programming Algorithm Using Least squares Subproblems

Download or read book A Strictly Improving Linear Programming Algorithm Using Least squares Subproblems written by Stephanie Leichner and published by . This book was released on 1993 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Linear Least Squares Computations

Download or read book Linear Least Squares Computations written by Farebrother and published by Routledge. This book was released on 2018-05-02 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting numerous algorithms in a simple algebraic form so that the reader can easilytranslate them into any computer language, this volume gives details of several methodsfor obtaining accurate least squares estimates. It explains how these estimates may beupdated as new information becomes available and how to test linear hypotheses.Linear Least Squares Computations features many structured exercises that guidethe reader through the available algorithms, plus a glossary of commonly used terms anda bibliography of supplementary reading ... collects "ancient" and modem results onlinear least squares computations in a convenient single source . . . develops the necessarymatrix algebra in the context of multivariate statistics . .. only makes peripheral use ofconcepts such as eigenvalues and partial differentiation .. . interprets canonical formsemployed in computation ... discusses many variants of the Gauss, Laplace-Schmidt,Givens, and Householder algorithms ... and uses an empirical approach for the appraisalof algorithms.Linear Least Squares Computations serves as an outstanding reference forindustrial and applied mathematicians, statisticians, and econometricians, as well as atext for advanced undergraduate and graduate statistics, mathematics, and econometricscourses in computer programming, linear regression analysis, and applied statistics.

Book Solving Least Squares Problems

Download or read book Solving Least Squares Problems written by Charles L. Lawson and published by SIAM. This book was released on 1995-12-01 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Classic edition includes a new appendix which summarizes the major developments since the book was originally published in 1974. The additions are organized in short sections associated with each chapter. An additional 230 references have been added, bringing the bibliography to over 400 entries. Appendix C has been edited to reflect changes in the associated software package and software distribution method.

Book Numerical Linear Algebra and Optimization

Download or read book Numerical Linear Algebra and Optimization written by Philip E. Gill and published by SIAM. This book was released on 2021-05-13 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classic volume covers the fundamentals of two closely related topics: linear systems (linear equations and least-squares) and linear programming (optimizing a linear function subject to linear constraints). For each problem class, stable and efficient numerical algorithms intended for a finite-precision environment are derived and analyzed. While linear algebra and optimization have made huge advances since this book first appeared in 1991, the fundamental principles have not changed. These topics were rarely taught with a unified perspective, and, somewhat surprisingly, this remains true 30 years later. As a result, some of the material in this book can be difficult to find elsewhere—in particular, techniques for updating the LU factorization, descriptions of the simplex method applied to all-inequality form, and the analysis of what happens when using an approximate inverse to solve Ax=b. Numerical Linear Algebra and Optimization is primarily a reference for students who want to learn about numerical techniques for solving linear systems and/or linear programming using the simplex method; however, Chapters 6, 7, and 8 can be used as the text for an upper-division course on linear least squares and linear programming. Understanding is enhanced by numerous exercises.

Book Mathematical Algorithms for Linear Regression

Download or read book Mathematical Algorithms for Linear Regression written by Helmuth Späth and published by Academic Press. This book was released on 2014-05-10 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Algorithms for Linear Regression discusses numerous fitting principles related to discrete linear approximations, corresponding numerical methods, and FORTRAN 77 subroutines. The book explains linear Lp regression, method of the lease squares, the Gaussian elimination method, the modified Gram-Schmidt method, the method of least absolute deviations, and the method of least maximum absolute deviation. The investigator can determine which observations can be classified as outliers (those with large errors) and which are not by using the fitting principle. The text describes the elimination of outliers and the selection of variables if too many or all of them are given by values. The clusterwise linear regression accounts if only a few of the relevant variables have been collected or are collectible, assuming that their number is small in relation to the number of observations. The book also examines linear Lp regression with nonnegative parameters, the Kuhn-Tucker conditions, the Householder transformations, and the branch-and-bound method. The text points out the method of least squares is mainly used for models with nonlinear parameters or for orthogonal distances. The book can serve and benefit mathematicians, students, and professor of calculus, statistics, or advanced mathematics.

Book A Strictly Improving Phase 1 Algorithm Using Least Squares Subproblems

Download or read book A Strictly Improving Phase 1 Algorithm Using Least Squares Subproblems written by and published by . This book was released on 1992 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although the simplex method's performance in solving linear programming problems is usually quite good, it does not guarantee strict improvement at each iteration on degenerate problems. Instead of trying to recognize and avoid degenerate steps in the simplex method (as some variants do), we have developed a new Phase I algorithm that is completely impervious to degeneracy, with strict improvement attained at each iteration. it is also noted that the new Phase I algorithm is closely related to a number of existing algorithms. When tested on the 30 smallest NETLIB linear programming test problems, the computational results for the new Phase I algorithm were almost 3. 5 times faster than the simplex method; on some problems, it was over 10 times faster.

Book Least Absolute Deviations

Download or read book Least Absolute Deviations written by P- Bloomfield and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: Least squares is probably the best known method for fitting linear models and by far the most widely used. Surprisingly, the discrete L 1 analogue, least absolute deviations (LAD) seems to have been considered first. Possibly the LAD criterion was forced into the background because of the com putational difficulties associated with it. Recently there has been a resurgence of interest in LAD. It was spurred on by work that has resulted in efficient al gorithms for obtaining LAD fits. Another stimulus came from robust statistics. LAD estimates resist undue effects from a feyv, large errors. Therefore. in addition to being robust, they also make good starting points for other iterative, robust procedures. The LAD criterion has great utility. LAD fits are optimal for linear regressions where the errors are double exponential. However they also have excellent properties well outside this narrow context. In addition they are useful in other linear situations such as time series and multivariate data analysis. Finally, LAD fitting embodies a set of ideas that is important in linear optimization theory and numerical analysis. viii PREFACE In this monograph we will present a unified treatment of the role of LAD techniques in several domains. Some of the material has appeared in recent journal papers and some of it is new. This presentation is organized in the following way. There are three parts, one for Theory, one for Applicatior.s and one for Algorithms.

Book Solving Least Squares Problems

Download or read book Solving Least Squares Problems written by Charles L. Lawson and published by SIAM. This book was released on 1995-12-01 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Numerical Linear Approximation in C

Download or read book Numerical Linear Approximation in C written by Nabih Abdelmalek and published by CRC Press. This book was released on 2008-05-19 with total page 964 pages. Available in PDF, EPUB and Kindle. Book excerpt: Illustrating the relevance of linear approximation in a variety of fields, Numerical Linear Approximation in C presents a unique collection of linear approximation algorithms that can be used to analyze, model, and compress discrete data. Developed by the lead author, the algorithms have been successfully applied to several engineering projects at the National Research Council of Canada. Basing most of the algorithms on linear programming techniques, the book begins with an introductory section that covers applications, the simplex method, and matrices. The next three parts focus on various L1, Chebyshev, and least squares approximations, including one-sided, bounded variables, and piecewise. The final section presents the solution of underdetermined systems of consistent linear equations that are subject to different constraints on the elements of the unknown solution vector. Except in the preliminary section, all chapters include the C functions of the algorithms, along with drivers that contain numerous test case examples and results. The accompanying CD-ROM also provides the algorithms written in C code as well as the test drivers. To use the software, it is not required to understand the theory behind each function.

Book A Strictly Improving Phase I Algoritm Using Least squares Subproblems

Download or read book A Strictly Improving Phase I Algoritm Using Least squares Subproblems written by Stanford University. Department of Operations Research. Systems Optimization Laboratory and published by . This book was released on 1992 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Finite Algorithms in Optimization and Data Analysis

Download or read book Finite Algorithms in Optimization and Data Analysis written by M. R. Osborne and published by . This book was released on 1985-12-23 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significance and originality of this book derive from its novel approach to those optimization problems in which an active set strategy leads to a finite algorithm, such as linear and quadratic programming or l1 and l approximations.

Book Optimization Software Guide

Download or read book Optimization Software Guide written by Jorge J. More and published by SIAM. This book was released on 1993-01-01 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developments in optimization theory, including emphasis on large problems and on interior-point methods for linear programming, have begun to appear in production software. Here is a reference tool that includes discussions of these areas and names software packages that incorporate the results of theoretical research. After an introduction to the major problem areas in optimization and an outline of the algorithms used to solve them, a data sheet is presented for each of the 75 software packages and libraries in the authors' survey. These include information on the capabilities of the packages, how to obtain them, and addresses for further information. Standard optimization paradigms are addressed -- linear, quadratic, and nonlinear programming; network optimization; unconstrained and bound-constrained optimization; least-squares problems; nonlinear equations; and integer programming. The most practical algorithms for the major fields of numerical optimization are outlined, and the software packages in which they are implemented are described. This format will aid current and potential users of optimization software in classifying the optimization problem to be solved, determining appropriate algorithms, and obtaining the software that implements those algorithms. Readers need only a basic knowledge of vector calculus and linear algebra to understand this book.

Book Stable and Efficient Solution of Weighted Least squares Problems with Applications in Interior Point Methods

Download or read book Stable and Efficient Solution of Weighted Least squares Problems with Applications in Interior Point Methods written by Patricia D. Hough and published by . This book was released on 1996 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: