A cutting planes algorithm based upon a semidefinite relaxation for the Quadratic Assignment Problem

Abstract

We present a cutting planes algorithm for the Quadratic Assignment Problem based upon a semidefinite relaxation, and we report experiments for classical instances. Our lower bound is compared with the ones obtained by linear and semidefinite approaches. Our tests show that the cuts we use (originally proposed for a linear approach) allow to improve significantly on the bounds obtained by the other approaches. Moreover, this is achieved within a moderate additional computing effort, and even in a shorter total time sometimes. Indeed, thanks to the strong tailing off effect of the SDP solver we have used (SB), we obtain in a reasonable time an approximate solution which is suitable to generate efficient cutting planes which speed up the convergence of SB. © Springer-Verlag Berlin Heidelberg 2005.