-Let (QP) be an integer quadratic program that consists in minimizing a quadratic functionsubject to linear constraints. To solve (QP), we reformulate it into an equivalent program with a convex objective function, and we use a Mixed Integer Quadratic Programming solver. This reformulation, called IQCR, is optimal in a certain sense from the continuous relaxation bound point of view. It is deduced from the solution of a SDP relaxation of (QP). Computational experiments are reported
Quadratic Convex Reformulation (QCR) is a technique that was originally proposed for 0-1 quadratic p...
Abstract. Many combinatorial optimization problems can be formulated as the minimization of a 0-1 qu...
We reformulate a (indefinite) quadratic program (QP) as a mixed-integer linear programming (MILP) pr...
We consider an integer program (QQP) where both the objective function and the constraints contain q...
We consider a general integer program (QQP) where both the objective function and the constraints ar...
-Let (QP) be a binary quadratic program that consists in minimizing a quadratic function subject to ...
We address the exact solution of general integer quadratic programs with linear constraints. These p...
Let (MQP) be a general mixed-integer quadratic program that consists of minimizing a quadratic funct...
AbstractLet (QP) be a 0-1 quadratic program which consists in minimizing a quadratic function subjec...
Abstract. In this paper, we consider problem (P ) of minimizing a quadratic function q(x)=xtQx+ctx o...
We consider problem (QP) of minimizing a quadratic function subject to linear or quadratic constrain...
Let View the MathML source be a 0-1 quadratic program which consists in minimizing a quadratic funct...
It is well known that semidefinite programming (SDP) can be used to derive useful relaxations for a ...
International audienceLet (QP) be a mixed integer quadratic program that consists of minimizing a qu...
Many combinatorial optimization problems can be formulated as the minimization of a 0?1 quadratic fu...
Quadratic Convex Reformulation (QCR) is a technique that was originally proposed for 0-1 quadratic p...
Abstract. Many combinatorial optimization problems can be formulated as the minimization of a 0-1 qu...
We reformulate a (indefinite) quadratic program (QP) as a mixed-integer linear programming (MILP) pr...
We consider an integer program (QQP) where both the objective function and the constraints contain q...
We consider a general integer program (QQP) where both the objective function and the constraints ar...
-Let (QP) be a binary quadratic program that consists in minimizing a quadratic function subject to ...
We address the exact solution of general integer quadratic programs with linear constraints. These p...
Let (MQP) be a general mixed-integer quadratic program that consists of minimizing a quadratic funct...
AbstractLet (QP) be a 0-1 quadratic program which consists in minimizing a quadratic function subjec...
Abstract. In this paper, we consider problem (P ) of minimizing a quadratic function q(x)=xtQx+ctx o...
We consider problem (QP) of minimizing a quadratic function subject to linear or quadratic constrain...
Let View the MathML source be a 0-1 quadratic program which consists in minimizing a quadratic funct...
It is well known that semidefinite programming (SDP) can be used to derive useful relaxations for a ...
International audienceLet (QP) be a mixed integer quadratic program that consists of minimizing a qu...
Many combinatorial optimization problems can be formulated as the minimization of a 0?1 quadratic fu...
Quadratic Convex Reformulation (QCR) is a technique that was originally proposed for 0-1 quadratic p...
Abstract. Many combinatorial optimization problems can be formulated as the minimization of a 0-1 qu...
We reformulate a (indefinite) quadratic program (QP) as a mixed-integer linear programming (MILP) pr...