考虑任务均衡的加油车动态调度问题

为了提高机场资源利用率以及航班的正点率,合理调度机场加油车为航班进行燃油加注服务势在必行。考虑到航班实际时刻的不可预知性,需建立动态规划时间窗,为窗口依据航班预计时刻捕捉到的航班构建机场车辆调度模型,利用自适应分支定价算法求解模型,从而配置车辆与人员,规划车辆的行驶路线,衔接任务,实现车辆行驶时间最短,加油员工作量均衡的目的。在华北某机场真实数据上进行仿真实验,结果表明,自适应分支定价算法优化下的车辆行驶时间与加油员工作量的标准差分较节约算法分别减小1.38%和7.47%,验证了算法的优势,且算法在机场其他地面服务规划问题中同样适用。

Dynamic refueling vehicle scheduling considering task balance

In order to improve the utilization rate of airport resources and the punctuality rate of flights, it is imperative to reasonably arrange airport refueling trucks to provide fuel refueling services for flights. Considering the unpredictability of the actual flight time, a dynamic planning time window needs to be established, and an airport vehicle scheduling model for is constructed for the window according to the flight captured at the estimated flight time. The model is solved by the adaptive branch pricing algorithm to configure vehicles and personnel, plan vehicle routes, and connect tasks, in order to achieve the purpose of minimal vehicle routes and balanced workloads of fuelers. Simulation experiments on the actual data of an airport in north China show that, compared with the saving algorithm, the adaptive branch pricing algorithm reduces the standard difference of travel time and workload by 1.38% and 7.41% respectively. The experiments verify the advantages of the algorithm, and the algorithm is also applicable to planning other airport ground service problems.