Applications of simulated annealing to global optimization problems with continuous variables

Global optimization problems with continuous variables are discussed based on simulated annealing. According to characteristics of the continuous variables, some practical methods for generating new points in a neighborhood 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.