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Titel:
Landscape statistics of the low autocorrelated
binary string problem
Author(s):
Fernando F. Ferreira,
José F.\ Fontanari,
Peter F. Stadler
Submitted to:
J. Phys. A: Math. Gen.
Abstract:
The statistical properties of the energy landscape of the low
autocorrelated binary string problem (LABSP) are studied
numerically and compared with those of several classic disordered
models. Using two global measures of landscape structure which have been
introduced in the Simulated Annealing literature, namely, depth and
difficulty, we find that the landscape of LABSP, except perhaps
for a very large degeneracy of the local minima energies, is qualitatively
similar to some well-known landscapes such as that of the mean-field 2-spin
glass model. Furthermore, we consider a mean-field approximation to the
pure model proposed by Bouchaud and Mézard (1994, J. Physique I
France 4 1109) and show both analytically and numerically that
it describes extremely well the statistical properties of LABSP.
Keywords:
Landscapes,
Low autocorrelated binary string problem,
Depth and Difficulty of Landscapes,
Metastable States
PACS Numbers 75.10.Nr, 05.50.+q, 64.60.Cn
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