An improved artificial immune algorithm

Analyze the reasons of the traditional artificial immune algorithm easily falling into local extreme point or premature convergence in the optimization process. A novel artificial immune algorithm, Adaptive Clone and Suppression Artificial Immune Algorithm (ACSAIA) is put forward. The proposed algorithm takes into account two factors of antibody affinity and concentration of antibody, and gives an adaptive operator to adjust them. Comparing with the corresponding evolutionary algorithm, ACSAIA can enhance the diversity of the population, avoid prematurity and solve deceptive problems to some extent. Moreover, the proposed algorithm has high convergence speed. The experiments show the proposed algorithm is superior to the traditional artificial immune algorithm and standard genetic algorithm in convergence speed and optimization performance.