The paper shows the contribution of evolutionary techniques in the field of optimization. Evolution is a technique which is based on real-world scenarios. It works on Darwin's theory and many algorithms have been proposed in this field to optimize the results. Each algorithm proposed has its advantages and disadvantages and a new technique is brought to overcome the drawbacks of the previously proposed technique. In this paper, a new approach is proposed based on SFLA and simulated annealing which works on memetic and PSO approaches along with basic temperature idea of simulated annealing. The graphs are attached to show the various results obtained. It is shown that it is better than other algorithms in various factors. © 2016 IEEE.