Collaborative Optimization Model for the Design and Operation of Feeder Bus Routes Based on Urban Metro
The collaborative development of conventional buses and urban metro has become an important research topic for the priority development of urban public transport. The topic of collaborative optimization of feeder bus route design and operation is studied in this study. The objective function is to m...
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2023/6987787 |
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| _version_ | 1832559175225311232 |
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| author | Yuanwen Lai Yansheng Chen |
| author_facet | Yuanwen Lai Yansheng Chen |
| author_sort | Yuanwen Lai |
| collection | DOAJ |
| description | The collaborative development of conventional buses and urban metro has become an important research topic for the priority development of urban public transport. The topic of collaborative optimization of feeder bus route design and operation is studied in this study. The objective function is to minimize the total travel time of passengers and the operation cost of feeder buses. The improved particle swarm optimization (PSO) algorithm is used to solve the collaborative optimization model, and the effectiveness of the model and algorithm is verified through the case study. The research shows that it is feasible in model construction and algorithm to carry out collaborative optimization of feeder bus route design and operation. Compared with the multiple-to-one (M to 1) mode, the multiple-to-multiple (M to M) mode can better satisfy the needs of passengers from different places of departure and destinations to achieve a more reasonable and realistic goal. The case study is based on two metro stations and 16 feeder bus stops on Fuzhou Metro line 2 to obtain two bus routes and a corresponding operation scheme. Under the same topology road network, the operation time of the improved PSO algorithm is much shorter than the DFS algorithm, the total cost error of the feeder bus is 0.04%, and the departure frequency error is 4.6%, which is within the reasonable error range. Therefore, the collaborative optimization model proposed in this study is feasible and effective in optimizing the feeder bus routes and operation. |
| format | Article |
| id | doaj-art-e05b4af6f565470f93fb8667cac4bfcc |
| institution | Kabale University |
| issn | 2042-3195 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-e05b4af6f565470f93fb8667cac4bfcc2025-02-03T01:30:44ZengWileyJournal of Advanced Transportation2042-31952023-01-01202310.1155/2023/6987787Collaborative Optimization Model for the Design and Operation of Feeder Bus Routes Based on Urban MetroYuanwen Lai0Yansheng Chen1College of Civil EngineeringCollege of Civil EngineeringThe collaborative development of conventional buses and urban metro has become an important research topic for the priority development of urban public transport. The topic of collaborative optimization of feeder bus route design and operation is studied in this study. The objective function is to minimize the total travel time of passengers and the operation cost of feeder buses. The improved particle swarm optimization (PSO) algorithm is used to solve the collaborative optimization model, and the effectiveness of the model and algorithm is verified through the case study. The research shows that it is feasible in model construction and algorithm to carry out collaborative optimization of feeder bus route design and operation. Compared with the multiple-to-one (M to 1) mode, the multiple-to-multiple (M to M) mode can better satisfy the needs of passengers from different places of departure and destinations to achieve a more reasonable and realistic goal. The case study is based on two metro stations and 16 feeder bus stops on Fuzhou Metro line 2 to obtain two bus routes and a corresponding operation scheme. Under the same topology road network, the operation time of the improved PSO algorithm is much shorter than the DFS algorithm, the total cost error of the feeder bus is 0.04%, and the departure frequency error is 4.6%, which is within the reasonable error range. Therefore, the collaborative optimization model proposed in this study is feasible and effective in optimizing the feeder bus routes and operation.http://dx.doi.org/10.1155/2023/6987787 |
| spellingShingle | Yuanwen Lai Yansheng Chen Collaborative Optimization Model for the Design and Operation of Feeder Bus Routes Based on Urban Metro Journal of Advanced Transportation |
| title | Collaborative Optimization Model for the Design and Operation of Feeder Bus Routes Based on Urban Metro |
| title_full | Collaborative Optimization Model for the Design and Operation of Feeder Bus Routes Based on Urban Metro |
| title_fullStr | Collaborative Optimization Model for the Design and Operation of Feeder Bus Routes Based on Urban Metro |
| title_full_unstemmed | Collaborative Optimization Model for the Design and Operation of Feeder Bus Routes Based on Urban Metro |
| title_short | Collaborative Optimization Model for the Design and Operation of Feeder Bus Routes Based on Urban Metro |
| title_sort | collaborative optimization model for the design and operation of feeder bus routes based on urban metro |
| url | http://dx.doi.org/10.1155/2023/6987787 |
| work_keys_str_mv | AT yuanwenlai collaborativeoptimizationmodelforthedesignandoperationoffeederbusroutesbasedonurbanmetro AT yanshengchen collaborativeoptimizationmodelforthedesignandoperationoffeederbusroutesbasedonurbanmetro |