In this paper we present an empirical study of the Negative Slope Coefficient (NSC) hardness statistic to characterize the difficulty of 3-SAT fitness landscapes for randomly generated problem instances. NSC correctly classifies problem instances with a low ratio of clauses to variables as easy, while instances with a ratio close to the critical point are classified as hard, as expected. Together with previous results on many different problems and fitness landscapes, the present results confirm that NSC is a useful and reliable indicator of problem difficulty. © 2008 Springer-Verlag Berlin Heidelberg.
Tomassini, M., Vanneschi, L. (2008). Negative Slope coefficient and the difficulty of random 3-SAT instances. In Applications of Evolutionary Computing. EvoWorkshops 2008 (pp.643-648). Berlin : Springer [10.1007/978-3-540-78761-7_70].
Negative Slope coefficient and the difficulty of random 3-SAT instances
VANNESCHI, LEONARDO
2008
Abstract
In this paper we present an empirical study of the Negative Slope Coefficient (NSC) hardness statistic to characterize the difficulty of 3-SAT fitness landscapes for randomly generated problem instances. NSC correctly classifies problem instances with a low ratio of clauses to variables as easy, while instances with a ratio close to the critical point are classified as hard, as expected. Together with previous results on many different problems and fitness landscapes, the present results confirm that NSC is a useful and reliable indicator of problem difficulty. © 2008 Springer-Verlag Berlin Heidelberg.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.