Optimizing Train-Set Circulation Plan in High-Speed Railway Networks Using Genetic Algorithm
As a sustainable transportation mode, high-speed railway (HSR) has been developing rapidly during the past decade in China. With the formation of dense HSR network, how to improve the utilization efficiency of train-sets (the carrying tools of HSR) has been a new research hotspot. Moreover, the emer...
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2019/8526953 |
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| author | Yun Wang Yu Zhou Xuedong Yan |
| author_facet | Yun Wang Yu Zhou Xuedong Yan |
| author_sort | Yun Wang |
| collection | DOAJ |
| description | As a sustainable transportation mode, high-speed railway (HSR) has been developing rapidly during the past decade in China. With the formation of dense HSR network, how to improve the utilization efficiency of train-sets (the carrying tools of HSR) has been a new research hotspot. Moreover, the emergence of railway transportation hubs has brought great challenges to the traditional train-sets’ utilization mode. Thus, in this paper, we address the issue of train-sets’ utilization problem with the consideration of railway transportation hubs, which consists of finding an optimal Train-set Circulation Plan (TCP) to complete trip tasks in a given Train Diagram (TD). An integer programming TCP model is established to optimize the train-set utilization scheme, aiming to obtain the one-to-one correspondence relationship among sets of train-sets, trip tasks, and maintenances. A genetic algorithm (GA) is designed to solve the model. A case study based on Nanjing and Shanghai HSR transportation hubs is made to demonstrate the practical significance of the proposed method. The results show that a more efficient TCP can be formulated by introducing train-sets being dispatched among different stations in the same hub. |
| format | Article |
| id | doaj-art-907fdfdf03504bedb42ac9bdb6d9ad75 |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-907fdfdf03504bedb42ac9bdb6d9ad752025-02-03T06:12:28ZengWileyJournal of Advanced Transportation0197-67292042-31952019-01-01201910.1155/2019/85269538526953Optimizing Train-Set Circulation Plan in High-Speed Railway Networks Using Genetic AlgorithmYun Wang0Yu Zhou1Xuedong Yan2MOT Key Laboratory of Transport Indcustry of Big Data Application Technologies for Comprehensive Transport, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaMOT Key Laboratory of Transport Indcustry of Big Data Application Technologies for Comprehensive Transport, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaMOT Key Laboratory of Transport Indcustry of Big Data Application Technologies for Comprehensive Transport, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, ChinaAs a sustainable transportation mode, high-speed railway (HSR) has been developing rapidly during the past decade in China. With the formation of dense HSR network, how to improve the utilization efficiency of train-sets (the carrying tools of HSR) has been a new research hotspot. Moreover, the emergence of railway transportation hubs has brought great challenges to the traditional train-sets’ utilization mode. Thus, in this paper, we address the issue of train-sets’ utilization problem with the consideration of railway transportation hubs, which consists of finding an optimal Train-set Circulation Plan (TCP) to complete trip tasks in a given Train Diagram (TD). An integer programming TCP model is established to optimize the train-set utilization scheme, aiming to obtain the one-to-one correspondence relationship among sets of train-sets, trip tasks, and maintenances. A genetic algorithm (GA) is designed to solve the model. A case study based on Nanjing and Shanghai HSR transportation hubs is made to demonstrate the practical significance of the proposed method. The results show that a more efficient TCP can be formulated by introducing train-sets being dispatched among different stations in the same hub.http://dx.doi.org/10.1155/2019/8526953 |
| spellingShingle | Yun Wang Yu Zhou Xuedong Yan Optimizing Train-Set Circulation Plan in High-Speed Railway Networks Using Genetic Algorithm Journal of Advanced Transportation |
| title | Optimizing Train-Set Circulation Plan in High-Speed Railway Networks Using Genetic Algorithm |
| title_full | Optimizing Train-Set Circulation Plan in High-Speed Railway Networks Using Genetic Algorithm |
| title_fullStr | Optimizing Train-Set Circulation Plan in High-Speed Railway Networks Using Genetic Algorithm |
| title_full_unstemmed | Optimizing Train-Set Circulation Plan in High-Speed Railway Networks Using Genetic Algorithm |
| title_short | Optimizing Train-Set Circulation Plan in High-Speed Railway Networks Using Genetic Algorithm |
| title_sort | optimizing train set circulation plan in high speed railway networks using genetic algorithm |
| url | http://dx.doi.org/10.1155/2019/8526953 |
| work_keys_str_mv | AT yunwang optimizingtrainsetcirculationplaninhighspeedrailwaynetworksusinggeneticalgorithm AT yuzhou optimizingtrainsetcirculationplaninhighspeedrailwaynetworksusinggeneticalgorithm AT xuedongyan optimizingtrainsetcirculationplaninhighspeedrailwaynetworksusinggeneticalgorithm |