The Fortran subroutine QL solves strictly convex quadratic programming problems subject to linear equality and inequality constraints by the primal-dual method of Goldfarb and Idnani. An available Cholesky decomposition of the objective function matrix can be provided by the user. Bounds are handled separately. The code is designed for solving small-scale quadratic programs in a numerically stable way. Its usage is outlined and an illustrative example is presented
-Let (QP) be an integer quadratic program that consists in minimizing a quadratic functionsubject to...
AbstractLet (QP) be a 0-1 quadratic program which consists in minimizing a quadratic function subjec...
In this paper we consider Quadratic Programming (QP) problems with general linear constraints. We sh...
We consider a general integer program (QQP) where both the objective function and the constraints ar...
An efficient and numerically stable dual algorithm for positive definite quadratic programming is de...
Philipp HungerländerKlagenfurt, Alpen-Adria-Univ., Dipl.-Arb., 2008KB2008 26(VLID)241275
Quadratic programming (QP) is one technique that allows for the optimization of a quadratic function...
Techniques for the preprocessing of (not-necessarily convex) quadratic programs are discussed. Most ...
We consider an integer program (QQP) where both the objective function and the constraints contain q...
This paper describes a new instance library for quadratic programming (QP), i.e., the family of cont...
Computational methods are considered for finding a point that satisfies the second-order necessary c...
A solution procedure for linear programs with one convex quadratic constraint is suggested. The meth...
This paper describes a method of minimizing a strictly convex quadratic functional of several variab...
Let View the MathML source be a 0-1 quadratic program which consists in minimizing a quadratic funct...
A algorithm for solving the definite quadratic programming problem is presented. An implementation ...
-Let (QP) be an integer quadratic program that consists in minimizing a quadratic functionsubject to...
AbstractLet (QP) be a 0-1 quadratic program which consists in minimizing a quadratic function subjec...
In this paper we consider Quadratic Programming (QP) problems with general linear constraints. We sh...
We consider a general integer program (QQP) where both the objective function and the constraints ar...
An efficient and numerically stable dual algorithm for positive definite quadratic programming is de...
Philipp HungerländerKlagenfurt, Alpen-Adria-Univ., Dipl.-Arb., 2008KB2008 26(VLID)241275
Quadratic programming (QP) is one technique that allows for the optimization of a quadratic function...
Techniques for the preprocessing of (not-necessarily convex) quadratic programs are discussed. Most ...
We consider an integer program (QQP) where both the objective function and the constraints contain q...
This paper describes a new instance library for quadratic programming (QP), i.e., the family of cont...
Computational methods are considered for finding a point that satisfies the second-order necessary c...
A solution procedure for linear programs with one convex quadratic constraint is suggested. The meth...
This paper describes a method of minimizing a strictly convex quadratic functional of several variab...
Let View the MathML source be a 0-1 quadratic program which consists in minimizing a quadratic funct...
A algorithm for solving the definite quadratic programming problem is presented. An implementation ...
-Let (QP) be an integer quadratic program that consists in minimizing a quadratic functionsubject to...
AbstractLet (QP) be a 0-1 quadratic program which consists in minimizing a quadratic function subjec...
In this paper we consider Quadratic Programming (QP) problems with general linear constraints. We sh...