A Clonal Chaos Adjustment Algorithm for multi-modal function optimization

By integrating chaos mechanism and niche technique, a novel immune algorithm - the clonal chaos adjustment algorithm (CCAA) is proposed based on the clonal selection principle and idiotypic immune network theory exhibited in biological immune system. Taking advantages of the ergodic and stochastic properties of chaotic variable, an adaptive chaos mutation operator is designed by the combination of prior knowledge of antibody and evolution iterations. The operator can avoid blind search effectively and enhance the convergence speed. By using stochastic processes martingale theory, the martingale characteristic of the average fitness of the population is analyzed and the almost sure strong convergence of CCAA is deduced. Furthermore, it is proved that the algorithm is globally convergent with probability 1 in a finite number of steps when the state space is finite. The simulation results of multi-modal function optimization show that CCAA can inhibit prematurity and has preferable global convergence performance.