A modified ant colony algorithm to solve the shortest path problem

Abstract

To solve the problem that the ant colony algorithm is easy to fall into local optimal solutions in solving the shortest path problem, improvements on the classical ant colony algorithm are provided in three aspects. Firstly, direction guiding is utilized in the initial pheromone concentration to speed up the initial convergence; secondly, the idea of pheromone redistribution is added to the pheromone partial renewal process in order to prevent the optimal path pheromone concentration from being over-damped by the path pheromone decay process; finally, a dynamic factor is invited to the global renewal process to adaptively update the pheromone concentration on the optimal path, in which way the global searching ability is improved. The results of the simulation experiment show that this modified algorithm can greatly increase the probability of finding the optimal path while guaranteeing the convergence speed.