New simulated annealing algorithms

This paper introduces a new class of D-dimensional density probability functions to be used in Simulated Annealing algorithms and derives an appropriate cooling schedule that is proved to be inversely proportional to a previously chosen power n of time. This generates a new algorithm, the nFast Simulated Annealing (nFSA), from which the Fast Simulated Annealing (FSA) is a particular case. As will be shown, this new algorithm achieves results with an accuracy that increases with n, at the expense of an initial convergence speed that decreases with n. This drawback is solved by the use of an adaptive algorithm, the Adaptive nFast Simulated Annealing (AnFSA), where the parameter n starts at small value, producing a fast initial convergence, and is raised as the algorithm runs, finding global minima points quickly and with great accuracy