Electric Transit Network Design by an Improved Artificial Fish-Swarm Algorithm
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 146, Issue 8
Abstract
This study solves the electric transit network design problem (ETNDP) by simultaneously optimizing the layout of bus routes, the service frequency, and the location of charging depots. To ensure the rational design and operational feasibility of an electric transit network, an optimization model of the ETNDP with the constraints of route, depot, operation, and charging is developed in consideration of achieving overall operating cost effectiveness, while guaranteeing adequate operating buses to meet all passenger demands and satisfy the recharging demands of all operating buses without delays or congestion. An improved artificial fish swarm algorithm (AFSA) with the crossover and mutation operators is developed to solve the proposed model. For example, the transit network in an urban region of a city in China is studied in this research. It is confirmed that the optimization model solved by the improved AFSA is able to appropriately provide the optimal solution to the design of a relatively large-scaled electric transit network for its efficient operation.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
This study is supported by the National Natural Science Foundation of China (Grant No. 71571011).
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 146 • Issue 8 • August 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: Jan 18, 2019
Accepted: Mar 2, 2020
Published online: May 28, 2020
Published in print: Aug 1, 2020
Discussion open until: Oct 28, 2020
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