I. Introduction
Artificial immune algorithm is a kind of stochastic optimization method based on the function, principles, basic features and related theory of biological immune system, which is put forward to solve the various complicated problerusl‘ [1]–[4] It has fast random global search capability, but can not make full use of the feedback information in the system, and its efficiency is low in some certain range when doing a lot of unnecessary redundant iteration. ACO (Ant Colony Optimization) is a kind of Bionic evolutionary algorithm put forward first by Dorigo [5]–[8]. The inspiration of ACO is from the behavior of Ant Colony'S looking for foods. It can not only solve the problems of static combinatorial optimization, but also those of dynamic combinatorial optimization. Its inherent parallelism, robustness, and other good characteristics make it a kind of effective calculation model which can solve complex optimization problems, but it also has some defects such as slowness, prematurely and stagnation.