A Comparative Study On The Application Of Ant Colony Algorithm,genetic Algorithm And The Fusion Of Two Methods In TSP

Traveling salesman problem(TSP)is a typical representative of combinatorial optimization problems,and it can solve many problems.With the extensive application of optimization theory in all walks of life,finding the optimal solution of traveling salesman problem becomes the focus of research.In this paper,the shortest path of the traveling salesman problem is studied.Firstly,this paper introduced the background and present situation of traveling salesman problem,and the ant colony algorithm,genetic algorithm and the fusion of two methods were introduced,the mathematical model and the steps of solving traveling salesman problem were established.Then,the research of the three algorithms in TSP were as follows:(1)The ant colony algorithm,genetic algorithm and the optimal parameter selection of the fusion were analyzed;(2)Under the condition of the optimal parameter selection,three algorithms are used to find the shortest path distance with changing the size of TSP;(3)The results of the three algorithms were compared and analyzed at different scales.The results showed: in the fact of finding the shortest path of TSP,When the TSP scale was small,there was no obvious difference among the three algorithms;With the expansion of the scale of TSP,the fusion of two methods was better than only using ant colony algorithm or genetic algorithm.