Improving the performance of standard solvers for quadratic 0-1 programs by a tight convex reformulation: The QCR method

Let ( QP ) be a 0-1 quadratic program which consists in minimizing a quadratic function subject to linear equality constraints. In this paper, we present QCR, a general method to reformulate ( QP ) into an equivalent 0-1 program with a convex quadratic objective function. The reformulated problem ca...

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Bibliographic Details
Published in:	Discrete Applied Mathematics Vol. 157; no. 6; pp. 1185 - 1197
Main Authors:	Billionnet, Alain, Elloumi, Sourour, Plateau, Marie-Christine
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 28.03.2009 Elsevier
Subjects:	Computational Complexity Computer Science Convex quadratic programming Densest [formula omitted]-subgraph Experiments Graph bisection Quadratic 0-1 programming Semidefinite programming Task allocation Semidefinite programming Densest k -subgraph Task allocation Quadratic 0-1 programming Convex quadratic programming Graph bisection Experiments Répartition des tâches Programmation quadratique convexe Programmation semi-définie K-sous-graphe plus dense Expériences Quadratique 0-1 programmation Densest k-subgraph Bissection graphique
ISSN:	0166-218X, 1872-6771
Online Access:	Get full text
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