基于运到期限的技术站动态配流优化研究

Dynamic Wagon-flow Allocation Based on Transit Period at Railway Technical Station

技术站配流作为货物运输的重要环节,影响着货物运输的时间和效率。为实现运到期限的兑现,以考虑运到期限的技术站动态配流为研究对象,将运到期限利用蒙特卡洛法分配到技术站转化为最大在站停留时间约束,引入优先级来评价货物的紧急程度,以优先级加权的货物总在站停留时间最小和发出总车辆数最多为双目标,为避免列车不合理停运,考虑不同满轴约束条件及摘挂、小运转列车可欠轴发出等车站实际,构建了混合整数规划模型,设计遗传模拟退火算法并采用软件求解。算例表明:与既有方法相比,研究的模型与算法能充分配流使得所有出发列车正点发出,优先处理优先级高的货物以减少其在站停留时间,且能保障所有货物不同运到期限的要求。

Wagon-flow allocation in railway technical stations,as an important part of cargo transportation,affects the delivery time and efficiency of cargo transportation.To guarantee the transit period,this paper took the dynamic wagonflow allocation in railway technical stations considering the transit period as the subject.The Monte Carlo method was utilized to allocate the transit period to the railway technical station and the transit period was converted into the maximum retention time constraint.The priority was introduced to evaluate the urgency of cargo.The dual objectives were the minimum priority-weighted total retention time and the maximum total number of departure trains.To avoid the unreasonable halt of trains,the paper built a mixed integer programming model considering the different size limitations of departure trains and the actual situation of the station that pick-up goods train and district transfer train can be sent out under axle.A genetic simulated annealing algorithm was designed and solved by MATLAB.The result of numerical examples demonstrates that compared with the available methods,the proposed model and algorithm can fully allocate wagon flow to dispatch all departure trains on time,prioritize the high-priority cargo,reduce their retention time at the station,and guarantee transit period.