A generalized simulated annealing approach to image reconstruction
Résumé
It is common pratice to speed-up simulated annealing by allowing the cost function and/or the candidate-solution generation mechanism to vary with temperature. We de- rive simple sufficient conditions for the global convergence of such generalized simulated annealing algorithms. These conditions are surprisingly weak; in particular, they do not involve the variations of the cost function with tempera-ture. We show that our results can be successfully applied to image reconstruction problems involving challenging optimization tasks.