Research On An Improved Genetic Algorithm And Soft Core Implementation

Genetic Algorithm (for short, GA) has made great achievements in the solution todifficult, complex problems, and can convergence to the global minimum. Howeversimple Genetic Algorithm likely to seek out a local optimum solution but a globalsub-optimization and has slow convergent speed at later evolution.For the purpose of prevention of premature phenomenon, acceleration ofconvergence, this paper proposed a new improved GA: Gradation Genetic Algorithm(for short, GGA). GGA marks off the population to sub-gradation for keep individualvariety. This method is proved effective through testing with typical function andcontrasting and analyzing the result. In order to make it more convenient for GA toapply on System On Programmable Chip (for short, SOPC), this paper explore GA softcore implementation base on Avalon bus. Experimentation simulation and performanceanalysis demonstrate feasibility and validity of the soft core implementation.