Master-to-slave nonlinear genetic algorithm

Through mechanism analysis of genetic algorithms (GAs), every genetic operator can be considered as a linear transform to the corresponding individuals. So some disadvantages of GAs such as premature convergence and calculation efficiency may be solved if genetic operators are modified to nonlinear transform. According to the above method, nonlinear genetic algorithm is introduced. By mechanism analysis of local search and global search capability of the genetic operators, master-to-slave nonlinear genetic algorithm is given in which nonlinear mutation operator owns global search capability only and lies in a different population. The optimization computing of some examples is made to show that the new genetic algorithm is useful and simple.