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Extending the QCR method to general mixed-integer programs

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Abstract

Let (MQP) be a general mixed integer quadratic program that consists of minimizing a quadratic function subject to linear constraints. In this paper, we present a convex reformulation of (MQP), i.e. we reformulate (MQP) into an equivalent program, with a convex objective function. Such a reformulation can be solved by a standard solver that uses a branch and bound algorithm. We prove that our reformulation is the best one within a convex reformulation scheme, from the continuous relaxation point of view. This reformulation, that we call MIQCR (Mixed Integer Quadratic Convex Reformulation), is based on the solution of an SDP relaxation of (MQP). Computational experiences are carried out with instances of (MQP) including one equality constraint or one inequality constraint. The results show that most of the considered instances with up to 40 variables can be solved in 1 h of CPU time by a standard solver.

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Authors and Affiliations

  1. CEDRIC-ENSIIE, 1 square de la résistance, 91025, Evry cedex, France

    Alain Billionnet

  2. CEDRIC-CNAM, 292 rue Saint-Martin, 75141, Paris cedex 03, France

    Sourour Elloumi & Amélie Lambert

Authors
  1. Alain Billionnet
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  2. Sourour Elloumi
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  3. Amélie Lambert
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Correspondence to Amélie Lambert.

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Billionnet, A., Elloumi, S. & Lambert, A. Extending the QCR method to general mixed-integer programs. Math. Program. 131, 381–401 (2012). https://doi.org/10.1007/s10107-010-0381-7

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  • DOI: https://doi.org/10.1007/s10107-010-0381-7

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