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Sequential Quadratic Programming Methods Based On Indefinite Hessian Approximations
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Book Synopsis Sequential Quadratic Programming Methods Based on Indefinite Hessian Approximations by : Meredith J. Goldsmith
Download or read book Sequential Quadratic Programming Methods Based on Indefinite Hessian Approximations written by Meredith J. Goldsmith and published by . This book was released on 1999 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Sequential Quadratic Programming with Indefinite Hessian Approximations for Nonlinear Optimum Experimental Design for Parameter Estimation in Differential-algebraic Equations by :
Download or read book Sequential Quadratic Programming with Indefinite Hessian Approximations for Nonlinear Optimum Experimental Design for Parameter Estimation in Differential-algebraic Equations written by and published by . This book was released on 2015 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Sequential Quadratic Programming Methods Based on Approximating a Projected Hessian Matrix (Classic Reprint) by : Chaya Bleich Gurwitz
Download or read book Sequential Quadratic Programming Methods Based on Approximating a Projected Hessian Matrix (Classic Reprint) written by Chaya Bleich Gurwitz and published by Forgotten Books. This book was released on 2018-02-14 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: Excerpt from Sequential Quadratic Programming Methods Based on Approximating a Projected Hessian Matrix We are interested in developing sequential quadratic programming methods which maintain an approximation to second derivative information projected onto the tangent space of the constraints. The main motivation for our work is that only the projected matrix enters into the optimality conditions for the nonlinear problem. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
Book Synopsis Sequential Quadratic Programming Methods Based on Approximating a Projected Hessian Matrix by : Chaya Bleich Gurwitz
Download or read book Sequential Quadratic Programming Methods Based on Approximating a Projected Hessian Matrix written by Chaya Bleich Gurwitz and published by Franklin Classics. This book was released on 2018-10-15 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Book Synopsis Sequential Quadratic Programming Methods Based on Approximating a Projected Hessian Matrix by : Chaya Bleich Gurwitz
Download or read book Sequential Quadratic Programming Methods Based on Approximating a Projected Hessian Matrix written by Chaya Bleich Gurwitz and published by . This book was released on 1986 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Large-scale Sequential Quadratic Programming Algorithms by :
Download or read book Large-scale Sequential Quadratic Programming Algorithms written by and published by . This book was released on 1992 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: The problem addressed is the general nonlinear programming problem: finding a local minimizer for a nonlinear function subject to a mixture of nonlinear equality and inequality constraints. The methods studied are in the class of sequential quadratic programming (SQP) algorithms, which have previously proved successful for problems of moderate size. Our goal is to devise an SQP algorithm that is applicable to large-scale optimization problems, using sparse data structures and storing less curvature information but maintaining the property of superlinear convergence. The main features are: 1. The use of a quasi-Newton approximation to the reduced Hessian of the Lagrangian function. Only an estimate of the reduced Hessian matrix is required by our algorithm. The impact of not having available the full Hessian approximation is studied and alternative estimates are constructed. 2. The use of a transformation matrix Q. This allows the QP gradient to be computed easily when only the reduced Hessian approximation is maintained. 3. The use of a reduced-gradient form of the basis for the null space of the working set. This choice of basis is more practical than an orthogonal null-space basis for large-scale problems. The continuity condition for this choice is proven. 4. The use of incomplete solutions of quadratic programming subproblems. Certain iterates generated by an active-set method for the QP subproblem are used in place of the QP minimizer to define the search direction for the nonlinear problem. An implementation of the new algorithm has been obtained by modifying the code MINOS. Results and comparisons with MINOS and NPSOL are given for the new algorithm on a set of 92 test problems.
Book Synopsis Numerical Optimization by : Jorge Nocedal
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 :Stanford University. Department of Operations Research. Systems Optimization Laboratory Publisher : ISBN 13 : Total Pages :98 pages Book Rating :4.F/5 ( download)
Book Synopsis Large-scale Sequential Quadratic Programming Algorithms by : Stanford University. Department of Operations Research. Systems Optimization Laboratory
Download or read book Large-scale Sequential Quadratic Programming Algorithms written by Stanford University. Department of Operations Research. Systems Optimization Laboratory and published by . This book was released on 1992 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Acta Numerica 2005: Volume 14 by : Arieh Iserles
Download or read book Acta Numerica 2005: Volume 14 written by Arieh Iserles and published by Cambridge University Press. This book was released on 2005-06-30 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: A high-impact factor, prestigious annual publication containing invited surveys by subject leaders: essential reading for all practitioners and researchers.
Book Synopsis Sequential Quadratic Programming Methods Based on Approximating a Projected Hessian Matrix - Primary Source Edition by : Chaya Bleich Gurwitz
Download or read book Sequential Quadratic Programming Methods Based on Approximating a Projected Hessian Matrix - Primary Source Edition written by Chaya Bleich Gurwitz and published by Nabu Press. This book was released on 2013-10 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a reproduction of a book published before 1923. This book may have occasional imperfections such as missing or blurred pages, poor pictures, errant marks, etc. that were either part of the original artifact, or were introduced by the scanning process. We believe this work is culturally important, and despite the imperfections, have elected to bring it back into print as part of our continuing commitment to the preservation of printed works worldwide. We appreciate your understanding of the imperfections in the preservation process, and hope you enjoy this valuable book.
Book Synopsis Second-derivative Sequential Quadratic Programming Methods for Nonlinear Optimization by : Vyacheslav Kungurtsev
Download or read book Second-derivative Sequential Quadratic Programming Methods for Nonlinear Optimization written by Vyacheslav Kungurtsev and published by . This book was released on 2013 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sequential Quadratic Programming (SQP) methods are a popular and successful class of methods for minimizing a generally nonlinear function subject to nonlinear constraints. Under a standard set of assumptions, conventional SQP methods exhibit a fast rate of local convergence. However, in practice, a conventional SQP method involves solving an indefinite quadratic program (QP), which is NP hard in general. As a result, approximations to the second-derivatives are often used, which can slow the rate of local convergence and reduce the chance that the algorithm will converge to a local minimizer instead of a saddle point. In addition, the standard assumptions required for convergence often do not hold in practice. For such problems, regularized SQP methods, which also require second-derivatives, have been shown to have good local convergence properties; however, there are few regularized SQP methods that exhibit convergence to a minimizer from an arbitrary initial starting point. This thesis considers the formulation, analysis and implementation of SQP methods with the following properties. (i) The solution of an indefinite QP is not required. (ii) Regularization is performed in such a way that global convergence can be established under standard assumptions. (iii) Implementations of the method work well on degenerate problems.
Book Synopsis Optimal Quadratic Programming Algorithms by : Zdenek Dostál
Download or read book Optimal Quadratic Programming Algorithms written by Zdenek Dostál and published by Springer Science & Business Media. This book was released on 2009-04-03 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quadratic programming (QP) is one advanced mathematical technique that allows for the optimization of a quadratic function in several variables in the presence of linear constraints. This book presents recently developed algorithms for solving large QP problems and focuses on algorithms which are, in a sense optimal, i.e., they can solve important classes of problems at a cost proportional to the number of unknowns. For each algorithm presented, the book details its classical predecessor, describes its drawbacks, introduces modifications that improve its performance, and demonstrates these improvements through numerical experiments. This self-contained monograph can serve as an introductory text on quadratic programming for graduate students and researchers. Additionally, since the solution of many nonlinear problems can be reduced to the solution of a sequence of QP problems, it can also be used as a convenient introduction to nonlinear programming.
Book Synopsis A Sequential Quadratic Programming Algorithm for Solving Large, Sparse Nonlinear Programs by : Ronald Harlan Nickel
Download or read book A Sequential Quadratic Programming Algorithm for Solving Large, Sparse Nonlinear Programs written by Ronald Harlan Nickel and published by . This book was released on 1984 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: This document describes the structure and theory for a sequential quadratic programming algorithm for solving large, sparse nonlinear optimization problems. Also provided are the details of a computer implementation of the algorithm, along with test results. The algorithm is based on Han's sequential quadratic programming method. It maintains a sparse approximation to the Cholesky factor of the Hessian of the Lagrangian and stores all gradients in a sparse format. The solution to the quadratic program generated at each step is obtained by solving the dual quadratic program using a projected conjugate gradient algorithm. Sine only active constraints are considered in forming the dual, the dual problem will normally be much smaller than the primal quadratic program and, hence, much easier to solve. An updating procedure is employed that does not destroy sparsity. Several test problems, ranging in size from 5 to 60 variables were solved with the algorithm. These results indicate that the algorithm has the potential to solve large, sparse nonlinear programs. The algorithm is especially attractive for solving problems having nonlinear constraints. (Author).
Book Synopsis Reduced Hessian Sequential Quadratic Programming Methods for Multidiscipline Design Optimization by : James P. Masciarelli
Download or read book Reduced Hessian Sequential Quadratic Programming Methods for Multidiscipline Design Optimization written by James P. Masciarelli and published by . This book was released on 1997 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Single-phase Method for Quadratic Programming by : Stanford University. Systems Optimization Laboratory
Download or read book A Single-phase Method for Quadratic Programming written by Stanford University. Systems Optimization Laboratory and published by . This book was released on 1986 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report describes a single-phase quadratic programming method, an active-set method which solves a sequence of equality-constraint quadratic programs.
Book Synopsis Inertia-controlling Methods for Quadratic Programming by : Philip E. Gill
Download or read book Inertia-controlling Methods for Quadratic Programming written by Philip E. Gill and published by . This book was released on 1988 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: We also derive recurrance relations that facilitate the efficient implementation of a class of inertia-controlling methods that maintain the factorization of a nonsingular matrix associated with the Karush-Kuhn-Tucker conditions."
Book Synopsis Schur-complement Method for Sparse Quadratic Programming by : Stanford University. Systems Optimization Laboratory
Download or read book Schur-complement Method for Sparse Quadratic Programming written by Stanford University. Systems Optimization Laboratory and published by . This book was released on 1987 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: Moreover, improvements in efficiency derived from exploiting new parallel and vector computer architectures are immediately applicable. An obvious application of the method is in sequential quadratic programming methods for nonlinearly constrained optimization, which require solution of a sequence of closely related quadratic programming subproblems. We discuss some ways in which the known relationship between successive problems can be exploited."
