GA is a method for solving optimization problems inspired by nature, and its processes are performed based on biological evolution. GA frequently changes the population of individual solutions of the problem (these changes are called evolution). At each step of this evolution, two members of the population were randomly chosen as parents, and children are considered as the next generation. Thus, the population evolves toward an optimal solution. The following steps shows the procedure by which GA solves problems: