An Urban Bus Network Generation Algorithm Based on Particle Swarm Optimization and Force Field Properties
Due to continuous urban sprawl, large-scale bus network design has become a major challenge in urban transport planning. The continuous increase in urban population and scale makes the factors considered in the urban route network design increasingly complex. Contemporary public transportation netwo...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
|
| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2022/6369217 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849467038715609088 |
|---|---|
| author | Yiming Chen Yanhong Gu Zhengdong Huang Tianhong Zhao Liangyuan Guo |
| author_facet | Yiming Chen Yanhong Gu Zhengdong Huang Tianhong Zhao Liangyuan Guo |
| author_sort | Yiming Chen |
| collection | DOAJ |
| description | Due to continuous urban sprawl, large-scale bus network design has become a major challenge in urban transport planning. The continuous increase in urban population and scale makes the factors considered in the urban route network design increasingly complex. Contemporary public transportation network design problems are based more on efficiency goals such as the accessibility and comfort of the transportation network, which increases the difficulty of analyzing the problem. Bus network design is not only an NP-hard (nondeterministic polynomial) problem but also a multivariable and multiobjective problem. This paper focuses on the bivariate and multiobjective bus network design problem of route generation and station selection. This paper proposes an algorithm called the Pseudo Force Field. By combining the idea of Particle Swarm Optimization (PSO) and the properties of the force field, a feasible route generation scheme is provided for the design of the bus network. The algorithm does not need to determine the end station and has a high degree of completion of the demand. This solves the problem of the selection of terminal stations in large-scale road network design. On this basis, the article combines Genetic Algorithm (GA) and Pareto frontier to provide a new route optimization algorithm and proves the effectiveness of the algorithm. The model has achieved theoretical results in the design of the bus route network in the megacity of Shenzhen, China. |
| format | Article |
| id | doaj-art-abbc010fa0c4498792499bb7ae44025c |
| institution | Kabale University |
| issn | 2042-3195 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-abbc010fa0c4498792499bb7ae44025c2025-08-20T03:39:14ZengWileyJournal of Advanced Transportation2042-31952022-01-01202210.1155/2022/6369217An Urban Bus Network Generation Algorithm Based on Particle Swarm Optimization and Force Field PropertiesYiming Chen0Yanhong Gu1Zhengdong Huang2Tianhong Zhao3Liangyuan Guo4College of Mathematics and StatisticsCollege of Mathematics and StatisticsResearch Institute for Smart CitiesResearch Institute for Smart CitiesCollege of Mathematics and StatisticsDue to continuous urban sprawl, large-scale bus network design has become a major challenge in urban transport planning. The continuous increase in urban population and scale makes the factors considered in the urban route network design increasingly complex. Contemporary public transportation network design problems are based more on efficiency goals such as the accessibility and comfort of the transportation network, which increases the difficulty of analyzing the problem. Bus network design is not only an NP-hard (nondeterministic polynomial) problem but also a multivariable and multiobjective problem. This paper focuses on the bivariate and multiobjective bus network design problem of route generation and station selection. This paper proposes an algorithm called the Pseudo Force Field. By combining the idea of Particle Swarm Optimization (PSO) and the properties of the force field, a feasible route generation scheme is provided for the design of the bus network. The algorithm does not need to determine the end station and has a high degree of completion of the demand. This solves the problem of the selection of terminal stations in large-scale road network design. On this basis, the article combines Genetic Algorithm (GA) and Pareto frontier to provide a new route optimization algorithm and proves the effectiveness of the algorithm. The model has achieved theoretical results in the design of the bus route network in the megacity of Shenzhen, China.http://dx.doi.org/10.1155/2022/6369217 |
| spellingShingle | Yiming Chen Yanhong Gu Zhengdong Huang Tianhong Zhao Liangyuan Guo An Urban Bus Network Generation Algorithm Based on Particle Swarm Optimization and Force Field Properties Journal of Advanced Transportation |
| title | An Urban Bus Network Generation Algorithm Based on Particle Swarm Optimization and Force Field Properties |
| title_full | An Urban Bus Network Generation Algorithm Based on Particle Swarm Optimization and Force Field Properties |
| title_fullStr | An Urban Bus Network Generation Algorithm Based on Particle Swarm Optimization and Force Field Properties |
| title_full_unstemmed | An Urban Bus Network Generation Algorithm Based on Particle Swarm Optimization and Force Field Properties |
| title_short | An Urban Bus Network Generation Algorithm Based on Particle Swarm Optimization and Force Field Properties |
| title_sort | urban bus network generation algorithm based on particle swarm optimization and force field properties |
| url | http://dx.doi.org/10.1155/2022/6369217 |
| work_keys_str_mv | AT yimingchen anurbanbusnetworkgenerationalgorithmbasedonparticleswarmoptimizationandforcefieldproperties AT yanhonggu anurbanbusnetworkgenerationalgorithmbasedonparticleswarmoptimizationandforcefieldproperties AT zhengdonghuang anurbanbusnetworkgenerationalgorithmbasedonparticleswarmoptimizationandforcefieldproperties AT tianhongzhao anurbanbusnetworkgenerationalgorithmbasedonparticleswarmoptimizationandforcefieldproperties AT liangyuanguo anurbanbusnetworkgenerationalgorithmbasedonparticleswarmoptimizationandforcefieldproperties AT yimingchen urbanbusnetworkgenerationalgorithmbasedonparticleswarmoptimizationandforcefieldproperties AT yanhonggu urbanbusnetworkgenerationalgorithmbasedonparticleswarmoptimizationandforcefieldproperties AT zhengdonghuang urbanbusnetworkgenerationalgorithmbasedonparticleswarmoptimizationandforcefieldproperties AT tianhongzhao urbanbusnetworkgenerationalgorithmbasedonparticleswarmoptimizationandforcefieldproperties AT liangyuanguo urbanbusnetworkgenerationalgorithmbasedonparticleswarmoptimizationandforcefieldproperties |