Research on Evolvable Hardware Based on Population Hybridization Monkey-King Genetic Algorithm

The evolution hardware as a new hardware carrier, having self-organizing, adaptive, self-repair ability, is an important application of artificial intelligence. Genetic algorithm is one of the important factors that influence the hardware evolution speed. For the problems of long evolutionary time and large amount of computation of traditional genetic algorithm, an improved genetic algorithm: Population Hybridization Monkey-King Genetic Algorithm was proposed. Inspired by hybrid vigor in biological species, gene sequences in Population Hybridization Monkey-King Genetic Algorithm were divided into independent evolution sub populations while evolving. Each sub population was formed by evolving according to Monkey-King Genetic Algorithm from the original population, the monkey king genes of sub populations were exchanged after Nd evolutions to be repeated Monkey King genetic operation, the off springs of heterosis were produced in sub population. Analysis shows that Population Hybridization Monkey-King Genetic Algorithm could reduce the computation of gene ordering in each generation to 1/ Nd comparing to Monkey-King Genetic Algorithm, and is more conducive to the realization of parallel. The simulation analysis based on MATLAB and Modelsim indicates that Population Hybridization Monkey-King Genetic Algorithm results in faster convergence speed and better evolution.