带时间窗车辆调度问题的蚁群算法

为求解带时间窗约束的配送中心车辆调度问题, 运用蚁群算法把时间窗约束转化为惩罚函数形式, 将其并入目标函数后, 建立了满足客户配送时间要求条件下的运输费用最低的车辆调度模型, 提出了模型的求解程序, 并以某算例进行了仿真分析。分析结果表明: 该模型通过参数的不同标定, 可以转化成旅行商模型、硬时间窗或软时间窗的车辆调度模型; 仿真算例中, 配送路线最优行驶距离为794 km, 车辆最长行驶时间为8.2 h, 该算法能有效求解配送中心车辆调度问题。

Ant colony algorithm of vehicle scheduling problem with time windows

In order to solve vehicle scheduling problem with time windows for distribution centers, time window constraint was transformed into penalty function based on ant colony algorithm, and penalty function was added to objective function.A vehicle routing model based on minimum transportation cost was built up to meet the customer requirements of delivery times, its solving program was designed, and a simulation example was studied.Analysis result indicates that the model can be transformed into traveling salesman problem (TSP) model and vehicle scheduling problem (VSP) model with hard-time window or soft-time window through different parameter calibrations.The optimal driving distance is 794 km, and the longest vehicle diving time is 8.2 h in the simulation example, so the ant colony algorithm can effectively solve the scheduling problems of distribution centers.