Ticket allocation and train stopping plans are important parts of railway transportation organization.At present,most of the ticket allocation plans are based on fixed train stopping plans,which limit the scope of tic...Ticket allocation and train stopping plans are important parts of railway transportation organization.At present,most of the ticket allocation plans are based on fixed train stopping plans,which limit the scope of ticket allocation.Trains can only serve passenger demands between stopping stations,leading to a loss of passenger demands at non-stopping stations,resulting in low seat occupancy rates and low revenue for railway enterprise.In order to better meet passenger demands,improve seat occupancy rates and increase the revenue of railway enterprises,this paper constructs a collaborative optimization model of ticket allocation and stopping plans based on stochastic demand and passenger choice behaviours in different time periods.Combined with CPLEX solver,the simulated annealing algorithm is designed to solve the problem.At the same time,new neighbourhood solution generation strategies of train stopping plans and ticket allocation plans under given stopping plans are designed.The experimental results show that in small-scale and large-scale experiments,the proposed method increases revenue by 0.14%and 9.09%,respectively,and effectively improves seat occupancy rates.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.72471247)the General Project of the Hunan Provincial Natural Science Foundation of China(Grant No.2022JJ30057)the Systematic Major Research Project of the China Railway(Grant No.P2022×012).
文摘Ticket allocation and train stopping plans are important parts of railway transportation organization.At present,most of the ticket allocation plans are based on fixed train stopping plans,which limit the scope of ticket allocation.Trains can only serve passenger demands between stopping stations,leading to a loss of passenger demands at non-stopping stations,resulting in low seat occupancy rates and low revenue for railway enterprise.In order to better meet passenger demands,improve seat occupancy rates and increase the revenue of railway enterprises,this paper constructs a collaborative optimization model of ticket allocation and stopping plans based on stochastic demand and passenger choice behaviours in different time periods.Combined with CPLEX solver,the simulated annealing algorithm is designed to solve the problem.At the same time,new neighbourhood solution generation strategies of train stopping plans and ticket allocation plans under given stopping plans are designed.The experimental results show that in small-scale and large-scale experiments,the proposed method increases revenue by 0.14%and 9.09%,respectively,and effectively improves seat occupancy rates.
