基于信息素异步更新的蚁群算法

针对基本蚁群算法中蚂蚁速度无限且信息素同步更新的假定前提,提出一种基于信息素异步更新的改进蚁群算法。该算法以蚂蚁的速度有限为前提,采用异步更新规则来调整各个蚂蚁的信息素浓度,从而间接改变蚂蚁间合作方式。该算法更忠实于实际蚁群的寻路过程,算法具有更好的全局搜索能力。基于旅行商问题的实验验证了算法的有效性、鲁棒性及解的多样性。

Ant colony optimization algorithm based on asynchronous update of pheromone

To deal with the assumptions in basic ant colony optimization (ACO) algorithm that the velocities of ants are infinite and pheromones of ants are updated synchronously, an improved ACO algorithm based on asynchronous update of pheromone is proposed. The algorithm, which assumes that the velocities of ants are finite, uses an asynchronous update rule to adjust pheromone concentration of each ant, thereby the cooperation of ants is changed indirectly. It conforms to the real ants system much better and has a better global searching ability. The experiments on traveling salesman problem prove the validity, robustness and solution diversity of the new algorithm.