Research of Multi-Population Immune Genetic Algorithm and Its Application in Multi-Model Function Optimization

摘要

A Multi-Population Immune Genetic Algorithm has been proposed in this paper. It adopts the Multi-Population policy to prevent premature convergence. The antibodies mutation mechanism is adopted to prevent the algorithm step in local optimal. It is unsupervised learning and easy to stabilization. When being used in function optimization, the results have shown that it has fascinating ability in function optimization.