TSP Problem Based on Artificial Ant Colony Algorithm

摘要

An Artificial ant colony algorithm is a swarm intelligence optimization algorithm is advanced and it is widely used in many fields. In this paper, the algorithm applied to the TSP problem solving, to construct the model of an artificial ant colony system, was designed to solve the model algorithm. With 31 capital cities of the latitude and longitude data as a sample, using MATLAB software empirical the application effect of artificial ant colony algorithm in solving the traveling salesman problem (TSP), and verified the superiority of the algorithm through way of seven kinds of algorithms are compared. The results show that the application of an artificial ant colony algorithm in solving TSP is feasible, and obtains the traversal of 31 provincial capital cities of the shortest distance 38884 km and the shortest path; in the operation time and optimal solution quality, artificial ant colony algorithm than the others algorithms perform a certain superiority.