Ant colony algorithm based on new pheromone updated strategy
基于新型信息素更新策略的蚁群算法*

This paper studied the routes searching strategy and the pheromone updating strategy of ant colony optimization algorithm (ACO) and ananlyzed the limitations of these strategies. To increase the performance of ACO, proposed the ant colony system based on improved pheromone updated strategy (PACS). Gave an example of traveling salesman problem, which was simulated by using basic ACO and PACS. The simulation results show that PACS has excellent global optimization properties and faster convergence speed, and it can avoid premature convergence of ACO.