F Altarelli et al 2008 J. Phys.: Conf. Ser. 95 012013 doi:10.1088/1742-6596/95/1/012013
F Altarelli1,2, R Monasson2 and F Zamponi2,3
Show affiliationsWe study the performances of stochastic heuristic search algorithms on Uniquely Extendible Constraint Satisfaction Problems with random inputs. We show that, for any heuristic preserving the Poissonian nature of the underlying instance, the (heuristic-dependent) largest ratio αa of constraints per variables for which a search algorithm is likely to find solutions is smaller than the critical ratio αd above which solutions are clustered and highly correlated. In addition we show that the clustering ratio can be reached when the number k of variables per constraints goes to infinity by the so-called Generalized Unit Clause heuristic.
05.40.-a Fluctuation phenomena, random processes, noise, and Brownian motion
05.20.-y Classical statistical mechanics
Issue 1 (2008)
F Altarelli et al 2008 J. Phys.: Conf. Ser. 95 012013
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