The Solution Of TSP Problem Base On Immune Algorithm

With developing in the field of research,ordinary algorithm can not meet people's requires.So Neural Networks Algorithm,Simulated Annealing Algorithm,Genetic Algorithm and Immune Algorithm come into being.In the sixty's,the research pioneers in the nature immune system research results were analyzed,with the help of science and technology,and the relevant content and knowledge,especially the theory and concept of genetics,the immune algorithm is successfully applied in some areas of Engineering Science,and received a good effect.As the genetic algorithm has the advantages of easy to use,strong robustness and easy to parallel processing,it is widely used in combination optimization,structural design,artificial intelligence and other fields.Traveling salesman problem,that is,the TSP problem(Salesman Problem Traveling)is one of the famous problems in the field of mathematics.Suppose there is a traveling merchant who wants to visit N cities,he must choose the path to go,the path of the limit is only a visit to each city,and finally to return to the original city.The path selection objective is the minimum value of the path that is required for all paths.This paper mainly refers to Immune Algorithm.At first,it gives us an all-round introduction of Immune Algorithm that contains basic concept and achievement steps.Then the author makes improvement of traditional Immune Algorithm.In this paper,the author has introduced several formulas.And then,the author combines them with Immune Algorithm.So there are several methods to solve problem of TSP.In the end,the author has tested several groups of data of Public Coordinate cities.