We consider the well-known minimum quadratic assignment problem. In this problem we are given two n × n nonnegative symmetric matrices A = (a_(ij)) and B = (b_(ij)). The objective is to compute a permutation π of V = {1,?,n} so that ~∑ i,jεV_(i≠j aπ(i),π(j)bi,j) is minimized. We assume that A is a 0/1 incidence matrix of a graph, and that B satisfies the triangle inequality. We analyze the approximability of this class of problems by providing polynomial bounded approximations for some special cases, and inapproximability results for other cases.
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