  The Rugged Metropolis (RM) algorithm is a biased updating scheme, which aims
at directly hitting the most likely configurations in a rugged free energy
landscape. Details of the one-variable (RM$_1$) implementation of this
algorithm are presented. This is followed by an extension to simultaneous
updating of two dynamical variables (RM$_2$). In a test with Met-Enkephalin in
vacuum RM$_2$ improves conventional Metropolis simulations by a factor of about
four. Correlations between three or more dihedral angles appear to prevent
larger improvements at low temperatures. We also investigate a multi-hit
Metropolis scheme, which spends more CPU time on variables with large
autocorrelation times.
