海铁联运一体化集装箱场站集卡调度研究OA
Research on the Truck Scheduling of Container Yard for Integrated Sea-Rail Intermodal Transport
海铁联运一体化集装箱场站依靠集卡进行水平转运作业,为缩短场站内部转运时间,提出海铁联运集装箱场站中铁路集卡与港口集卡联合调度的新思路.基于海铁一体化发展导向,尝试不再区分铁路集卡、港口集卡,通过港铁平台公司投入采购共享集卡,用于整个联运组织的任意水平运输任务,优化转运换装环节,缩短集装箱在港内的流转时间,提高集卡利用率.研究以集卡派遣成本、空车运行成本与时间窗惩罚成本整体最小作为优化目标建立整数规划模型,并利用数学软件编写遗传算法求解集卡调度模型,对算例进行研究分析,得到最优集卡联合调度方案.同时,对遗传算法个体编码方式进行特别设计,使算法与问题间更为适配.通过对比实验可以得出,联合调度方案在一定程度上降低了运输成本,证明了该方案的可行性与优越性.
As container yards of integrated sea-rail intermodal transportation rely on trucks for horizontal transfer operations,in order to shorten the internal transfer time for the yards and improve the utilization rate of trucks,a new idea of joint scheduling of railway and port trucks was proposed.Based on the orientation to sea-rail intermodal transport integration,this paper,rather than attempted to distinguish between railway and port trucks,invested in purchasing shared trucks through port-rail platform companies for any level of transportation task of the entire intermodal transportation organization,to optimize the sea-rail transportation and loading process and shorten the container circulation time in the port,thus improving the utilization rate of trucks.This paper established an integer programming model with a view to overall minimum of truck scheduling cost,empty vehicle operation cost,and time window penalty cost as the optimization objective.And the genetic algorithm was written using MATLAB software to solve the truck scheduling model,with further research and analysis conducted on examples to obtain the optimal truck joint scheduling plan.Besides,a special design has been made for the individual encoding method of the genetic algorithm to make the algorithm more adaptable to the problem.It is concluded through comparative experiments that the joint scheduling scheme has reduced transportation costs to a certain extent,proving its feasibility and superiority.
张铁金
中国国家铁路集团有限公司 办公厅,北京 100844
交通运输
海铁联运集装箱场站集卡调度模型联合调度遗传算法
Sea-Rail Intermodal TransportationContainer YardTruck Scheduling ModelJoint SchedulingGenetic Algorithm
《铁道运输与经济》 2024 (002)
54-61 / 8
中国国家铁路集团有限公司科技研究开发计划课题(K2021X017)
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