Guided simulated annealing method for optimization problems

Incorporating the concept of order parameter of the mean-field theory into the simulated annealing method, we present an 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 identifies global minima for several difficult optimization problems. Application of this method to the HP lattice-protein model has found another lowest-energy state for an N=100 sequence that was not found by other methods before. Results for spin glass models are also presented which show improvement over the previous results.