Add to ORKGThe idea of solving the definite linear complementarity problem by successive overrelaxation was originally proposed by Cryer. Hildreth and d'Esopo presented a Gauss-Seidel-like iterative method to solve a quadratic programming prob lern. In this paper a detailed discussion of Cryer's method applied to quadratic programming problems is given. The convergence behaviour is treated without assumptions on solvability of the problem. Numerical examples indicate the efficiency of the method
The problem of determining whether quadratic programming models possess either unique or multiple op...
The problem of determining whether quadratic programming models possess either unique or multiple op...
Solution of dynamic optimization problems by successive quadratic programming and orthogonal colloca...
By perturbing a linear program to a quadratic program it is possible to solve the latter in its dual...
A parallel successive overrelaxation (SOR) method is proposed for the solution of the fundamental sy...
A parallel successive overrelaxation (SOR) method is proposed for the solution of the fundamental sy...
A parallel successive overrelaxation (SOR) method is proposed for the solution of the fundamental sy...
By perturbing a linear program to a quadratic program, it is possible to solve the latter in its dua...
A gradient projection successive overrelaxation (GP-SOR) algorithm is proposed for the solution of s...
A gradient projection successive overrelaxation (GP-SOR) algorithm is proposed for the solution of s...
A gradient projection successive overrelaxation (GP-SOR) algorithm is proposed for the solution of s...
A solution procedure for linear programs with one convex quadratic constraint is suggested. The meth...
The global convergence properties of a class of penalty methods for nonlinear pro-gramming are analy...
A well-known approach to the solution of large and sparse linearly constrained quadratic programming...
A well-known approach to the solution of large and sparse linearly constrained quadratic programming...
The problem of determining whether quadratic programming models possess either unique or multiple op...
The problem of determining whether quadratic programming models possess either unique or multiple op...
Solution of dynamic optimization problems by successive quadratic programming and orthogonal colloca...
By perturbing a linear program to a quadratic program it is possible to solve the latter in its dual...
A parallel successive overrelaxation (SOR) method is proposed for the solution of the fundamental sy...
A parallel successive overrelaxation (SOR) method is proposed for the solution of the fundamental sy...
A parallel successive overrelaxation (SOR) method is proposed for the solution of the fundamental sy...
By perturbing a linear program to a quadratic program, it is possible to solve the latter in its dua...
A gradient projection successive overrelaxation (GP-SOR) algorithm is proposed for the solution of s...
A gradient projection successive overrelaxation (GP-SOR) algorithm is proposed for the solution of s...
A gradient projection successive overrelaxation (GP-SOR) algorithm is proposed for the solution of s...
A solution procedure for linear programs with one convex quadratic constraint is suggested. The meth...
The global convergence properties of a class of penalty methods for nonlinear pro-gramming are analy...
A well-known approach to the solution of large and sparse linearly constrained quadratic programming...
A well-known approach to the solution of large and sparse linearly constrained quadratic programming...
The problem of determining whether quadratic programming models possess either unique or multiple op...
The problem of determining whether quadratic programming models possess either unique or multiple op...
Solution of dynamic optimization problems by successive quadratic programming and orthogonal colloca...