Solving urban electric transit network problem by integrating Pareto artificial fish swarm algorithm and genetic algorithm
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.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/15472450
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Supplemental Notes:
- © 2020 Taylor & Francis Group, LLC 2020. Abstract reprinted with permission of Taylor & Francis.
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Authors:
- Liu, Yi
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0000-0002-6861-2914
- Feng, Xuesong
- Yang, Yan
- Ruan, Zejing
- Zhang, Lukai
- Li, Kemeng
- Publication Date: 2022-5
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 253-268
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Serial:
- Journal of Intelligent Transportation Systems
- Volume: 26
- Issue Number: 3
- Publisher: Taylor & Francis
- ISSN: 1547-2450
- EISSN: 1547-2442
- Serial URL: http://www.tandfonline.com/loi/gits20
Subject/Index Terms
- TRT Terms: Electric vehicle charging; Genetic algorithms; Networks; Optimization; Public transit; Routes; Urban areas
- Geographic Terms: China
- Subject Areas: Public Transportation; Terminals and Facilities; Vehicles and Equipment;
Filing Info
- Accession Number: 01850305
- Record Type: Publication
- Files: TRIS
- Created Date: Jun 27 2022 5:19PM