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Simulated Annealing is one of the important evolutionary algorithms which can be used in many applications especially in optimization problems. Simulated Annealing has two main phases, the first one is annealing schedule and the second is acceptance probability function. I proposed three annealing schedule methods and one acceptance probability function. The idea of adding momentum terms was used to improve speed and accuracy of annealing schedulers and prevent extreme changes in values of acceptance probability function. Some of my proposed methods show a good accuracy and the others make significant improvement in the speed of simulated Annealing algorithms than the original functions which have been used in the original simulated annealing algorithm.