Research and Application of an Improved Ant Colony Algorithm

Abstract

Ant colony algorithm is a bionic algorithm which is used to optimize the shortest path in graph. But the traditional ant colony algorithm has some disadvantages, such as slow convergence speed, easy to fall into local optimum, high complexity and so on. In this paper, it focus on the problems of slow convergence speed and easily falling into local optimum and contribute the local pheromone updating strategy and global pheromone updating strategy, it also optimize the routing formula and local search method after analyzing the problems. It conducts some simulation experiments about our optimization scheme and the traditional ant colony algorithm in Matlab environment, by comparing the results of experiments, the optimization scheme proposed can get a better search path in different examples and the μ (t) function can effectively reduce iterations.