  Incorporating the concept of order parameter of the mean-field theory into
the simulated annealing method, we presented a new optimization algorithm, the
guided simulated annealing method.
  In this method mean-field order parameters are calculated to guide the
configuration search for the global minimum. Allowing fluctuations and
improvement of mean-field values iteratively, this method successfully
identified global minima for several difficult optimization problems.
Application of this method to the HP lattice-protein model has found a new
lowest energy state for an $N = 100$ sequence that was not found by other
methods before. Results for spin glass models are also presented.
