Chaos Immune Algorithm and its application to function optimization

This paper combines chaos operator with Immune Algorithm, and advances Chaos Immune Algorithm. In this algorithm, the ergodic property of chaos phenomenon was used to optimize the initial antibody population. Through the clone selection operator, mutation operator and recruited antibody, local optimums were avoided, so the global optimization was obtained. Through the algorithm performance analysis, comparison with the genetic algorithm and its application to multi-peak function optimization, the optimization calculating result shows that Chaos Immune Algorithm can be assured of the global optimal solution, and greatly increase optimization speed.