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Convex reformulations for binary quadratic programs

Abstract : -Let (QP) be a binary quadratic program that consists in minimizing a quadratic function subject to linear constraints. To solve (QP) we reformulate it into an equivalent program with a convex objective function. Our reformulation, that we call EQCR (Extended Quadratic Convex Reformulation), is optimal from the continuous relaxation bound point of view. We show that this best reformulation can be deduced from the solution of a semidefinite relaxation of (QP) and that EQCR outperforms QCR. We carry out computational experiments on Max-Cut and on the k-cluster problem.
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Submitted on : Friday, March 6, 2015 - 11:21:58 AM
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  • HAL Id : hal-01125632, version 1



Alain Billionnet, Sourour Elloumi, Amélie Lambert. Convex reformulations for binary quadratic programs. EURO 2009, 23rd European Conference on Operational Research, Jul 2009, Bonn, Germany. pp.47. ⟨hal-01125632⟩



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