Research into Optimization Algorithm Based on Immune Mechanism

摘要

Based on immune mechanism a novel optimization algorithm is presented. By defining and regulating the antibody density, the diversity of the algorithmic population is improved. Three funtions from different definitions of antibody density are deduced and compared with their convergent efficiencies. Theoretical analysis proves that the algorithm is convergent. Experimental results show that the algorithm has a better searching ability and quicker convergent speed than GA. The problem of premature convergence can be alleviated in the algorithm.