Abstract
Computer network route optimization has been a subject of more attention in the art. This article routing optimization issues in-depth study of the ant colony algorithm to solve distributed parallelism, and propose measures for improvement ant colony algorithm node state transition rule. Pheromone updated rules and improved the classical ant colony algorithm performance. Simulation results show that the improved ant colony algorithm proposed in this paper can change according to the constraints, preferably the most appropriate routing information. Meanwhile, after two improvements, ant colony algorithm convergence rate may be raised, the probability fall into local extreme is also greatly reduced, more conducive to large-scale computer network routing optimization problem.
