Simulated Annealing (SA) algorithm was originally inspired from the metal work annealing process. This algorithm was designed to be implemented in the combinatorial optimization problems and it has been adapted to be implemented for continuous optimization problems. In this algorithm, a new point is randomly generated in each iteration. The distance of the new point generated in each iteration from the current point or to the extent of the search space is measured based on the probability distribution using a scale proportional to the temperature. The algorithm allows all new points that lower the objective and also points that raise the objective with a certain point probability. By accepting points that raise the objective, this algorithm is able to escape from being trapped inside the local minima and it is able to explore globally for more feasible solutions in the search space.