A Single Phased Method For Quadratic Programming
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Author | : Stanford University. Systems Optimization Laboratory |
Publisher | : |
Total Pages | : 80 |
Release | : 1986 |
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This report describes a single-phase quadratic programming method, an active-set method which solves a sequence of equality-constraint quadratic programs.
Author | : Stephen Carey Hoyle |
Publisher | : |
Total Pages | : 250 |
Release | : 1985 |
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Author | : Edward Joseph Wiest |
Publisher | : |
Total Pages | : 25 |
Release | : 1990 |
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Author | : |
Publisher | : Stanford University |
Total Pages | : 128 |
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Author | : Yves Dominique Brise |
Publisher | : Logos Verlag Berlin GmbH |
Total Pages | : 232 |
Release | : 2013 |
Genre | : Computers |
ISBN | : 3832533664 |
This PhD thesis was written at ETH Zurich, in Prof. Dr. Emo Welzl's research group, under the supervision of Dr. Bernd Garnter. It shows two theoretical results that are both related to quadratic programming. The first one concerns the abstract optimization framework of violator spaces and the randomized procedure called Clarkson's algorithm. In a nutshell, the algorithm randomly samples from a set of constraints, computes an optimal solution subject to these constraints, and then checks whether the ignored constraints violate the solution. If not, some form of re-sampling occurs. We present the algorithm in the easiest version that can still be analyzed successfully. The second contribution concerns quadratic programming more directly. It is well-known that a simplex-like procedure can be applied to quadratic programming. The main computational effort in this algorithm comes from solving a series of linear equation systems that change gradually. We develop the integral LU decomposition of matrices, which allows us to solve the equation systems efficiently and to exploit sparse inputs. Last but not least, a considerable portion of the work included in this thesis was devoted to implementing the integral LU decomposition in the framework of the existing quadratic programming solver in the Computational Geometry Algorithms Library (CGAL). In the last two chapters we describe our implementation and the experimental results we obtained.
Author | : Zdenek Dostál |
Publisher | : Springer Science & Business Media |
Total Pages | : 293 |
Release | : 2009-04-03 |
Genre | : Mathematics |
ISBN | : 0387848061 |
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.
Author | : Philip E. Gill |
Publisher | : |
Total Pages | : 48 |
Release | : 1988 |
Genre | : Quadratic programming |
ISBN | : |
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."
Author | : Elizabeth Lai Sum Wong |
Publisher | : |
Total Pages | : 125 |
Release | : 2011 |
Genre | : |
ISBN | : 9781124691152 |
Computational methods are considered for finding a point satisfying the second-order necessary conditions for a general (possibly nonconvex) quadratic program (QP). A framework for the formulation and analysis of feasible-point active-set methods is proposed for a generic QP. This framework is defined by reformulating and extending an inertia-controlling method for general QP that was first proposed by Fletcher and subsequently modified by Gould. This reformulation defines a class of methods in which a primal-dual search pair is the solution of a "KKT system'' of equations associated with an equality-constrained QP subproblem defined in terms of a "working set'' of linearly independent constraints. It is shown that, under certain circumstances, the solution of this KKT system may be updated using a simple recurrence relation, thereby giving a significant reduction in the number of systems that need to be solved. The use of inertia control guarantees that the KKT systems remain nonsingular throughout, thereby allowing the utilization of third-party linear algebra software. The algorithm is suitable for indefinite problems, making it an ideal QP solver for stand-alone applications and for use within a sequential quadratic programming method using exact second derivatives. The proposed framework is applied to primal and dual quadratic problems, as well as to single-phase problems that combine the feasibility and optimality phases of the active-set method, producing a range of formats that are suitable for a variety of applications. The algorithm is implemented in the Fortran code icQP. Its performance is evaluated using different symmetric and unsymmetric linear solvers on a set of convex and nonconvex problems. Results are presented that compare the performance of icQP with the convex QP solver SQOPT on a large set of convex problems.
Author | : Stanford University. Department of Operations Research. Systems Optimization Laboratory |
Publisher | : |
Total Pages | : 142 |
Release | : 1991 |
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Author | : |
Publisher | : |
Total Pages | : 892 |
Release | : 1994 |
Genre | : Aeronautics |
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