基于公共订舱的铁路客车化集装箱班列舱位分配研究OA

With the transformation and upgrading of railway freight towards modern logistics,the railway has introduced a passenger-style container block train product that allows customers to book slots in advance.However,the traditional first-come first-served(FCFS)slot allocation strategy cannot fully utilize transportation resources,resulting in railway revenue loss.In view of the organization mode of block trains for passenger-style public booking,a collaborative slot allocation strategy of"phased admission+nested protection"(PA-NP)was designed.By considering constraints such as train slot capacity and cargo owners'timeliness demands,a stochastic programming model aiming at maximizing railway revenue was constructed.The slot allocation scheme was solved by calling the Gurobi solver via Python,and sensitivity analyses were conducted on the admission proportion of each sales period and the intensity of nested protection.The results show that the revenue of the PA-NP strategy increases by 60.8%and 21.4%compared with FCFS and single phased admission(PA),respectively.Scientifically dividing sales periods and setting moderate nested protection levels can effectively improve railway transportation revenue,providing a theoretical basis and decision support for railway freight enterprises to implement refined revenue management and formulate scientific slot allocation schemes.