Education S ystem Search : A N ew P opulation - based M etaheuristic O ptimization A lgorithm

Optimization algorithms inspired by nature as intelligent optimization methods with classical methods have demonstrated significant success. Some of these te chniques are genetic algorithms, inspired by biological evolution of humans and other creatu res) ant colony optimization and s imulated annealing method (i nspired by the refrigeration process metals). The methods for solving optimization problems in many different areas such as determining the optimal course of their work, designing optimal control for industrial processes, solving industrial engineering major issues such as the optimal layout design for industrial units, problem solving, and queuing i n th e design of intelligent agents have been used. This paper introduces a new algorithm for optimization, which is not a natural phenomenon, but a phenomenon inspired teaching - human. It is entitled Education System algorithm (ESA). Results demonstrate this method is better than other method in this area