Decomposition and Linearization for 0-1 Quadratic Programming

Sourour Elloumi, Alain Faye and Eric Soutif

Annals of Operations Research, 2000, vol. 99, issue 1, 79-93

Abstract: This paper presents a general decomposition method to compute bounds for constrained 0-1 quadratic programming. The best decomposition is found by using a Lagrangian decomposition of the problem. Moreover, in its simplest version this method is proved to give at least the bound obtained by the LP-relaxation of a non-trivial linearization. To illustrate this point, some computational results are given for the 0-1 quadratic knapsack problem. Copyright Kluwer Academic Publishers 2000

Keywords: quadratic 0-1 programming; mixed integer programming; Lagrangian decomposition; linearization (search for similar items in EconPapers)
Date: 2000
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DOI: 10.1023/A:1019236832495

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