Novel Chaos Immune Optimization Combination Algorithm

Making use of the ergodicity and internal randomicity of chaos iteration,a novel chaos immune algorithm(CIA) is presented to improve the convergence performance of the immune evolutionary algorithm.The presented algorithm integrates advantages of the immune evolutionary algorithm(IEA) and chaos optimization algorithm(COA).Chaos variables are loaded into the variable colony of immune algorithm in the immune evolutionary algorithm,and tiny disturbance is added to the memory colony and the disturbance amplitude is gradually adjusted by virtue of the characteristic of chaos search.The experimental results indicate that the algorithm can remarkably improve the convergence performance and search efficiency of the immune evolutionary algorithm.