抄録
In this paper, we propose a so-called n-state ant colony algorithm for efficiently solving the crossbar switching problem. In the proposed algorithm, n kinds of pheromone and n kinds of heuristic information are introduced to reinforce the search ability. The conception of the n-state ant colony algorithm provides a novel searching mechanism. In order to evaluate the n-state ant colony algorithm for solving the crossbar switching problem, a large number of simulations are performed, and some other algorithms are used for comparison. The simulation results show that the proposed n-state ant colony algorithm performs remarkably well and outperforms its competitors.
