Sequential Quadratic Programming Algorithms For Optimization
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Sequential Quadratic Programming Algorithms For Optimization
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Author : Francisco Javier Prieto
language : en
Publisher:
Release Date : 1989
Sequential Quadratic Programming Algorithms For Optimization written by Francisco Javier Prieto and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with categories.
Large Scale Sequential Quadratic Programming Algorithms
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Author : Stanford University. Department of Operations Research. Systems Optimization Laboratory
language : en
Publisher:
Release Date : 1992
Large Scale Sequential Quadratic Programming Algorithms written by Stanford University. Department of Operations Research. Systems Optimization Laboratory and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with categories.
Large Scale Sequential Quadratic Programming Algorithms
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Author :
language : en
Publisher:
Release Date : 1992
Large Scale Sequential Quadratic Programming Algorithms written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with categories.
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.
Encyclopedia Of Optimization
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Author : Christodoulos A. Floudas
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-09-04
Encyclopedia Of Optimization written by Christodoulos A. Floudas and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-04 with Mathematics categories.
The goal of the Encyclopedia of Optimization is to introduce the reader to a complete set of topics that show the spectrum of research, the richness of ideas, and the breadth of applications that has come from this field. The second edition builds on the success of the former edition with more than 150 completely new entries, designed to ensure that the reference addresses recent areas where optimization theories and techniques have advanced. Particularly heavy attention resulted in health science and transportation, with entries such as "Algorithms for Genomics", "Optimization and Radiotherapy Treatment Design", and "Crew Scheduling".
Sequential Quadratic Programming Algorithm Using An Incomplete Solution Of The Subproblem
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Author : Stanford University. Department of Operations Research. Systems Optimization Laboratory
language : en
Publisher:
Release Date : 1990
Sequential Quadratic Programming Algorithm Using An Incomplete Solution Of The Subproblem written by Stanford University. Department of Operations Research. Systems Optimization Laboratory and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with categories.
Scientific And Technical Aerospace Reports
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Author :
language : en
Publisher:
Release Date : 1990
Scientific And Technical Aerospace Reports written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Aeronautics categories.
A Sequential Quadratic Programming Algorithm For Solving Large Sparse Nonlinear Programs
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Author : Ronald Harlan Nickel
language : en
Publisher:
Release Date : 1984
A Sequential Quadratic Programming Algorithm For Solving Large Sparse Nonlinear Programs written by Ronald Harlan Nickel and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984 with Mathematical optimization categories.
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).
Sequential Quadratic Programming Algorithm Using An Incomplete Solution Of The Subproblem
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Author : Stanford University. Department of Operations Research. Systems Optimization Laboratory
language : en
Publisher:
Release Date : 1993
Sequential Quadratic Programming Algorithm Using An Incomplete Solution Of The Subproblem written by Stanford University. Department of Operations Research. Systems Optimization Laboratory and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with categories.
Optimal Quadratic Programming Algorithms
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Author : Zdenek Dostál
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-04-03
Optimal Quadratic Programming Algorithms written by Zdenek Dostál and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-03 with Mathematics categories.
Solving optimization problems in complex systems often requires the implementation of advanced mathematical techniques. Quadratic programming (QP) is one technique that allows for the optimization of a quadratic function in several variables in the presence of linear constraints. QP problems arise in fields as diverse as electrical engineering, agricultural planning, and optics. Given its broad applicability, a comprehensive understanding of quadratic programming is a valuable resource in nearly every scientific field. Optimal Quadratic Programming Algorithms presents recently developed algorithms for solving large QP problems. The presentation 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. The reader is required to have a basic knowledge of calculus in several variables and linear algebra.
A Sequential Quadratic Programming Algorithm Using An Incomplete Solution Of The Subproblem
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Author :
language : en
Publisher:
Release Date : 1993
A Sequential Quadratic Programming Algorithm Using An Incomplete Solution Of The Subproblem written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with categories.
We analyze sequential quadratic programming (SQP) methods to solve nonlinear constrained optimization problems that are more flexible in their definition than standard SQP methods. The type of flexibility introduced is motivated by the necessity to deviate from the standard approach when solving large problems. Specifically we no longer require a minimizer of the QP subproblem to be determined or particular Lagrange multiplier estimates to be used. Our main focus is on an SQP algorithm that uses a particular augmented Lagrangian merit function. New results are derived for this algorithm under weaker conditions than previously assumed; in particular, it is not assumed that the iterates lie on a compact set.