基于改进蚁群算法的空铁联运路径自动控制方法

Automatic route control method of air rail intermodal transportation based on improved ant colony algorithm

路径规划一直是制约空铁联运发展的难题之一,一旦路径规划不合理,付出的经济成本就会大大提高。针对上述问题,提出一种基于改进蚁群算法的空铁联运路径自动控制方法。在该研究中描述空铁联运路径问题,构建空铁联运网络模型,并为此作出6项假设。以航空运输成本、铁路运输成本、转运成本、惩罚成本组成空铁联运总成本,并以最小值作为目标函数模型。为模型设置交通流量守恒、交通工具唯一性、运输时间、货物转运次数等4个约束条件;在约束条件,利用改进蚁群算法求取模型最优解。结果表明:与rank-Wolfe算法、K短路算法、基本蚁群算法相比,利用改进蚁群算法求出的空铁联运路径应用下,所要花费的总成本要更少,说明改进蚁群算法求出的解更优,更能控制运输成本,实现经济运输。

Path planning has always been one of the difficult problems restricting the development of air rail intermodal transportation.Once the path planning is unreasonable,the economic cost will be greatly increased.To solve the above problems,an automatic route control method for air rail intermodal transportation based on improved ant colony algorithm is proposed.In this study,the air rail intermodal transport path problem is described,the air rail intermodal transport network model is constructed,and six hypotheses are made.The total cost of air rail intermodal transportation is composed of air transportation cost,railway transportation cost,transshipment cost and penalty cost,and the minimum value is taken as the objective function model.Set up four constraints for the model,such as traffic flow conservation,uniqueness of vehicles,transportation time and times of goods transfer;Under the constraints,the improved ant colony algorithm is used to obtain the optimal solution of the model.The results show that compared with rank Wolfe algorithm,k-short circuit algorithm and basic ant colony algorithm,the total cost of air rail intermodal transportation path calculated by improved ant colony algorithm is less,which shows that the solution obtained by improved ant colony algorithm is better,can better control transportation cost and realize economic transportation.