An Immune Optimal Algorithm and Its Application

An immune algorithm of a mathematically optimal structure model is derived based on the natural immune system mechanism. The algorithm combines the evolution function of traditional genetic algorithms and the density mechanism in creatures’immune procedure. The adjustment of antibodies is realized by the expected breed rate to improve the premature convergence. The algorithm is used to solve for the optimization of Rosenbrock function, and compared to a genetic algorithm. The results show that the immune algorithm performs better in the aspect of global and local search ability and search speed