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We describe Fortran subroutines for finding approximate solutions of sparse instances of the Quadratic Assignment Problem (QAP) using a Greedy Randomized Adaptive Search Procedure (GRASP). The design and implementation of the code are described in detail. Computational results comparing the new subroutines with a dense version of the code (Algorithm 754, ACM TOMS) show that the speedup increases with the sparsity of the data.
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Pardalos et al. (1997) studied this question.
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