原文传递
Solving urban electric transit network problem by integrating Pareto artificial fish swarm algorithm and genetic algorithm
| 题名： | Solving urban electric transit network problem by integrating Pareto artificial fish swarm algorithm and genetic algorithm |
| 正文语种： | eng |
| 作者： | Yi Liu;Xuesong Feng;Yan Yang;Zejing Ruan;Lukai Zhang;Kemeng Li |
| 作者单位： | School of Traffic and Transportation Beijing Jiaotong University;School of Traffic and Transportation Beijing Jiaotong University;Guangxi Traffic Technician College;School of Traffic and Transportation Beijing Jiaotong University;School of Traffic and Transportation Beijing Jiaotong University;School of Traffic and Transportation Beijing Jiaotong University |
| 关键词： | Artificial fish swarm algorithm;charging station location;frequency setting;multi-objective optimization;transit network design |
| 摘要： | Abstract This study presents a multi-objective optimization model for the urban electric transit network problem with the aim of simultaneously designing the layout of bus routes, the frequency and the location and size of charging stations by making a tradeoff between two inconsistent objectives from the perspectives of passengers and operators. A Pareto artificial fish swarm algorithm (PAFSA) embedded with the genetic algorithm (GA) is developed to solve the proposed model. The PAFSA is designed to iteratively search for the proper network configuration satisfying two conflicting objectives. During which, the demand assignment with real-time transit information is performed to update the frequency of each newly designed route. The GA embedded into the PAFSA iteratively decides the locations of charging stations and the number of chargers to be installed in each charging station. A case study of the transit network in an urban region of a city in China is implemented, revealing that the proposed approach is able to rationally design a relatively large-scaled transit network with searching for the best fits between two inconsistent objectives. |
| 出版年： | 2022 |
| 期刊名称： | Journal of Intelligent Transportation Systems |
| 卷： | 26 |
| 期： | 1/6 |
| 页码： | 258-273 |
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