
handle: 10630/5171
In this article we provide an exact expression for computing the autocorrelation coefficient $\xi$ and the autocorrelation length $\ell$ of any arbitrary instance of the Quadratic Assignment Problem (QAP) in polynomial time using its elementary landscape decomposition. We also provide empirical evidence of the autocorrelation length conjecture in QAP and compute the parameters $\xi$ and $\ell$ for the 137 instances of the QAPLIB. Our goal is to better characterize the difficulty of this important class of problems to ease the future definition of new optimization methods. Also, the advance that this represents helps to consolidate QAP as an interesting and now better understood problem. Spanish Ministry of Science and Innovation and FEDER under contract TIN2008-06491-C04-01 (M* project) and the Andalusian Government under contract P07-TIC-03044 (DIRICOM project).
Elementary landscapes, elementary landscapes, Autocorrelation length, 330, Applied Mathematics, fitness landscapes, autocorrelation length, 004, Discrete location and assignment, quadratic assignment problem, Quadratic assignment problem, autocorrelation coefficient, Fitness landscapes, Autocorrelación (Estadística), Autocorrelation coefficient
Elementary landscapes, elementary landscapes, Autocorrelation length, 330, Applied Mathematics, fitness landscapes, autocorrelation length, 004, Discrete location and assignment, quadratic assignment problem, Quadratic assignment problem, autocorrelation coefficient, Fitness landscapes, Autocorrelación (Estadística), Autocorrelation coefficient
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