Optimal Problem Research Base On Artificial Immune Algorith

One of the obvious characters of modern science and technology's development is that life science and engineering science promoting, permeating and crossing each other. As we known, biological immune system is a highly parallel adaptive information learning system, which can identify and remove the antigenic eyewinkers invading the body. This system can learn, remember and adjust adaptively to keep the stabilization inside the body. Biological immune system contains plenty of information processing information processing mechanisms. Through researching, we can design many models and algorithms to solve many complex problems, and it is of great significant to many engineering technology researching.First of all, some basic concepts, framework, functions and principles of the biological immune system are introduced; Then the research range, research status and basic theory of the artificial immune system are simply analyzed. And this paper introduces the AIS definition, and simply concludes there search origin and contents of AIS.And then the article introduced the elements and basic implement technology of Immune Algorithms, and expatiated the specialty of Immune Algorithms expressly. The basic configuration and flow of Immune Algorithms which are come up are researched. Just case of the knowledge of the above deficiency and in order to meet the realistic needs, the paper expects to present the general model of the immune system, advance some algorithms and explore more application fields.Lastly, this paper applies Rosenbrock function seeking extremum and Immune Algorithm to Traveling Salesman Problem, a kind of typical combinational optimization problems. We confirm important factors that influence the algorithm characteristics and get the ranges of the parameters byexperiments. Comparing the algorithm with other algorithms, the results show that the convergent speed of the algorithm is faster than others.Researches in the paper which enrich theory and application of immune algorithm, and bring new technique to solve Traveling Salesman problem, have theoretical value and practical significance. But as a new intelligent technology, it lacks of systematism and a united general model. Moreover, it should be applied to more real-world fields. Some algorithms should also get improved.