Generalized simulated annealing

We discuss and illustrate a new stochastic algorithm (generalized simulated annealing) for computationally finding the global minimum of a given (not necessarily convex) energy/cost function defined in a continuous D-dimensional space. This algorithm recovers, as particular cases, the so-called classical (“Boltzmann machine”) and fast (“Cauchy machine”) simulated annealings, and turns out to be quicker than both