A Heuristic Immune-Genetic Algorithm for Multimodal Function Optimization

To avoid premature convergence and guarantee the diversity of the population, a heuristic immune-genetic algorithm (HIGA) is proposed. Rapid immune response (secondary response), adaptive mutation and density operators in the HIGA are emphatically designed to improve the searching ability, greatly increase the converging speed, and avoid locating the local maxima due to the premature convergence. The simulation results show that HIGA converges rapidly, guarantees the diversity, stability and good searching ability