基于改进蚁群算法在粮食物流配送路径优化的应用研究

Application research on quantum ant colony algorithm in grain logistics distribution path optimization

为了有效地降低粮食的运输成本,提出了一种改进的蚁群算法对粮食物流配送路径进行优化。该算法通过改进蚂蚁的转移规则、初始化信息素和全局信息素以及增加各条路径信息量调整的局部更新规则。仿真实验结果表明,改进的蚁群算法比基本蚁群算法可以更好地解决粮食物流配送路径优化问题,路径长度明显缩短,从而使有限的资源发挥更大的作用。

A modified ant colony algorithm was proposed to optimize grain logistics distribution path in order to reduce transportation cost effectively. The proposed algorithm adjusted local update rules via the following ways, such as improvement transition rule of the ant, initialization pheromone and global pheromone as well as increase the amount of information of each path. The simulation results showed that the modified algorithm provided a better solution in grain logistics distribution path optimization than the basic ant colony algorithm. It can cut down path length and therefore play a bigger role in utilization of the limited resources.