Y. Li, P.M. Pardalos, K.G. Ramakrishnan, and M.G.C. Resende
Annals of Operations Research, vol. 50, pp. 387-411, 1994
ABSTRACT
We investigate the classical Gilmore-Lawler lower
bound for the quadratic assignment problem. We provide evidence of
the difficulty of improving the Gilmore-Lawler Bound and develop new
bounds by means of optimal reduction schemes. Computational
results are reported indicating that the new lower bounds have
advantages over previous bounds and can be used in a branch-and-bound
type algorithm for the quadratic assignment problem.
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