Application of Intelligence Algorithm on TSP ----Based on the Data the Cities in Guangdong

Abstract

In this paper, we applied four intelligent algorithms into solving the classic Traveling Salesman Problem (TSP). By drawing comparisons and analysis on the pros and cons of this four algorithms, TSP problem can be better solved. This paper begins with the discussion of the background and principles of four algorithms; and goes into the discussion on their performance when applied onto solving a practical problem of Guangdong province tourist rout planning project. Index Terms - TSP, intelligence algorithm, tourist rout planning. I. Background and Significance of Topics Path planning problem, including Traveling Salesman Problem (TSP), Vehicle Path Planning problem (VRP), is a topic on which many domestic and foreign scholars have done a lot of researches. Previous research focus was mainly on finding the shortest path algorithm, such as Dijkstra's algorithm, Floyd-Warshall algorithm, etc. Starting in 1956 when Artificial Intelligence was formally put on the table as a newly born subject, many intelligent algorithms has been applied to TSP problem, such as Artificial Neural Networks, Ant Colony Optimization algorithm, Genetic Algorithm, Particle Swarm Optimization algorithm and Artificial Immune System, etc. Intelligent optimization algorithms provide a new train of thought. Although intelligent optimization algorithms cannot assure a global optimization result, it can get the result in a short time for solving large-scale problems. In this paper, Dijkstra's algorithm and Floyd-Warshall algorithm are used to calculate the shortest distance between any two vertices in a given figure. On this basis, GA, SAA, ACA, PSO algorithms were applied to further solve the path selection. II . Algorithm principles