An　ACO　(Ant　Colony　Optimization)　algorithm　for　TSP　(Traveling　Salesman　Problem)　with　knowledge　guiding　pheromone　control　strategy　is　put　forward.　On　the　one　hand,　aiming　at　accelerating　the　convergence,　the　pheromone　is　initialized　by　the　MST　(Minimal　Spanning　Tree)　information.　On　the　other　hand,　the　pheromone　updating　is　guided　by　swarm　knowledge,　which　is　the　intersection　information　of　paths　constructed　by　all　ants.　It　can　strengthen　the　collaboration　of　ants.　The　experimental　results　indicate　that　the　proposed　algorithm　outperforms　other　ACO　algorithms.