Adaptive immune-genetic algorithm for global optimization to multivariable function

An adaptive immune-genetic algorithm (AlGA) is proposed to avoid premature convergence and guarantee the diversity of the population. Rapid immune response (secondary response), adaptive mutation and density operators in the AlGA are emphatically designed to improve the searching ability, greatly increase the converging speed, and decrease locating the local maxima due to the premature convergence. The simulation results obtained from the global optimization to four multivariable and multi-extreme functions show that AlGA converges rapidly, guarantees the diversity, stability and good searching ability.