The complexity of quadratic programming problems with two quadratic constraints is an open problem. In this paper we show that when one constraint is a ball constraint and the Hessian of the quadratic function defining the other constraint is positive definite, then, under quite general conditions, the problem can be solved in polynomial time in the real-number model of computation through an approach based on the analysis of the dual space of the Lagrange multipliers. However, the degree of the polynomial is rather large, thus making the result mostly of theoretical interest
In Chapter 2 of the thesis, we study cut generating functions for conic sets. Our first main result ...
Quadratic programs are generally hard and difficult to solve, where many instances are known to be N...
We consider a fractional programming problem that minimizes the ratio of two indefinite quadratic fu...
Caption title.Includes bibliographical references.This research is partially supported by the U.S. A...
AbstractThe complexity of linearly constrained (nonconvex) quadratic programming is analyzed within ...
preprintWe consider the exact solution of problem $(QP)$ that consists in minimizing a quadratic fun...
Many problems in economics, statistics and numerical analysis can be formulated as the optimization ...
AbstractLagrangian duality underlies many efficient algorithms for convex minimization problems. A k...
SoumisNational audienceThis paper presents new semidefinite programming bounds for 0-1 quadratic pro...
Cataloged from PDF version of article.In this paper a simple derivation of duality is presented for ...
AbstractWe are concerned in this paper with techniques for computing upper bounds on the optimal obj...
Two important topics in the study of Quadratically Constrained Quadratic Programming (QCQP) are how ...
AbstractA convex quadratic program has Kuhn-Tucker conditions which are necessary and sufficient, an...
In this paper we combine an infeasible Interior Point Method (IPM) with the Proximal Method of Multi...
We prove a sufficient global optimality condition for the problem of minimizing a quadratic function...
In Chapter 2 of the thesis, we study cut generating functions for conic sets. Our first main result ...
Quadratic programs are generally hard and difficult to solve, where many instances are known to be N...
We consider a fractional programming problem that minimizes the ratio of two indefinite quadratic fu...
Caption title.Includes bibliographical references.This research is partially supported by the U.S. A...
AbstractThe complexity of linearly constrained (nonconvex) quadratic programming is analyzed within ...
preprintWe consider the exact solution of problem $(QP)$ that consists in minimizing a quadratic fun...
Many problems in economics, statistics and numerical analysis can be formulated as the optimization ...
AbstractLagrangian duality underlies many efficient algorithms for convex minimization problems. A k...
SoumisNational audienceThis paper presents new semidefinite programming bounds for 0-1 quadratic pro...
Cataloged from PDF version of article.In this paper a simple derivation of duality is presented for ...
AbstractWe are concerned in this paper with techniques for computing upper bounds on the optimal obj...
Two important topics in the study of Quadratically Constrained Quadratic Programming (QCQP) are how ...
AbstractA convex quadratic program has Kuhn-Tucker conditions which are necessary and sufficient, an...
In this paper we combine an infeasible Interior Point Method (IPM) with the Proximal Method of Multi...
We prove a sufficient global optimality condition for the problem of minimizing a quadratic function...
In Chapter 2 of the thesis, we study cut generating functions for conic sets. Our first main result ...
Quadratic programs are generally hard and difficult to solve, where many instances are known to be N...
We consider a fractional programming problem that minimizes the ratio of two indefinite quadratic fu...