Application of simulated annealing to global optimization problems with continuous variables

Global optimization problems with continuous variables were discussed based on simulated annealing. Implementation steps were given. Practical methods of determining control parameters were introduced. According to characteristics of continuous variables, practical methods of generating new points from a current point were given. Finally, an example of computing the fundamental matrix in computer vision domain was given to demonstrate the application to continuous variables. The simulation results showed that the algorithm can efficiently solve the global optimization problems with continuous variables.