An Optimization Method of Multiclass Price Railway Passenger Transport Ticket Allocation under High Passenger Demand
The development of high-speed railways (HSR) in China has attracted a large number of passengers from highway and aviation to railways due to their comfort and high speed. In this case, HSR passenger transportation can improve the operating income by optimizing the ticket allocation. Here, we propos...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2020/8860115 |
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| author | Bin Wang Shaoquan Ni Fucai Jin Zixu Huang |
| author_facet | Bin Wang Shaoquan Ni Fucai Jin Zixu Huang |
| author_sort | Bin Wang |
| collection | DOAJ |
| description | The development of high-speed railways (HSR) in China has attracted a large number of passengers from highway and aviation to railways due to their comfort and high speed. In this case, HSR passenger transportation can improve the operating income by optimizing the ticket allocation. Here, we propose an optimization method of multiclass price railway passenger transport ticket allocation under high passenger demand. First, for the “censored data” problem in the railway passenger demand forecast, we constructed an unconstrained model of railway passenger demand and solved the unconstrained demand through an expectation-maximization algorithm. Then, on this basis, we use gray neural networks (GNNs) to predict the passenger demand of different origins and destinations (ODs), and according to the prediction results, we propose two ticket allocation methods based on operation and capacity control: accurate predivided model and fuzzy predivided model. And we solve this problem by constructing a particle swarm optimization algorithm. Lastly, we use examples to prove that the proposed ticket allocation method can meet the passengers’ needs and have good economic benefits. |
| format | Article |
| id | doaj-art-5142b91ea5b9433ca3dff6ef434db21c |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-5142b91ea5b9433ca3dff6ef434db21c2025-02-03T06:46:08ZengWileyJournal of Advanced Transportation0197-67292042-31952020-01-01202010.1155/2020/88601158860115An Optimization Method of Multiclass Price Railway Passenger Transport Ticket Allocation under High Passenger DemandBin Wang0Shaoquan Ni1Fucai Jin2Zixu Huang3School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, ChinaSchool of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, ChinaInstitute of Computing Technologies, China Academy of Railway Sciences Corporation Limited, Beijing 100081, ChinaSchool of Civil Engineering and Transportation, South China University of Technology, Guangzhou, Guangdong 510640, ChinaThe development of high-speed railways (HSR) in China has attracted a large number of passengers from highway and aviation to railways due to their comfort and high speed. In this case, HSR passenger transportation can improve the operating income by optimizing the ticket allocation. Here, we propose an optimization method of multiclass price railway passenger transport ticket allocation under high passenger demand. First, for the “censored data” problem in the railway passenger demand forecast, we constructed an unconstrained model of railway passenger demand and solved the unconstrained demand through an expectation-maximization algorithm. Then, on this basis, we use gray neural networks (GNNs) to predict the passenger demand of different origins and destinations (ODs), and according to the prediction results, we propose two ticket allocation methods based on operation and capacity control: accurate predivided model and fuzzy predivided model. And we solve this problem by constructing a particle swarm optimization algorithm. Lastly, we use examples to prove that the proposed ticket allocation method can meet the passengers’ needs and have good economic benefits.http://dx.doi.org/10.1155/2020/8860115 |
| spellingShingle | Bin Wang Shaoquan Ni Fucai Jin Zixu Huang An Optimization Method of Multiclass Price Railway Passenger Transport Ticket Allocation under High Passenger Demand Journal of Advanced Transportation |
| title | An Optimization Method of Multiclass Price Railway Passenger Transport Ticket Allocation under High Passenger Demand |
| title_full | An Optimization Method of Multiclass Price Railway Passenger Transport Ticket Allocation under High Passenger Demand |
| title_fullStr | An Optimization Method of Multiclass Price Railway Passenger Transport Ticket Allocation under High Passenger Demand |
| title_full_unstemmed | An Optimization Method of Multiclass Price Railway Passenger Transport Ticket Allocation under High Passenger Demand |
| title_short | An Optimization Method of Multiclass Price Railway Passenger Transport Ticket Allocation under High Passenger Demand |
| title_sort | optimization method of multiclass price railway passenger transport ticket allocation under high passenger demand |
| url | http://dx.doi.org/10.1155/2020/8860115 |
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