Maximizing Ridership through Integrated Bus Service Considering Travel Demand Elasticity with Genetic Algorithm
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 147, Issue 4
Abstract
Developing efficient operational strategies to improve service quality of bus transit, such as reducing travel time, can stimulate ridership. A mathematical model is formulated to optimize integrated bus service which maximizes ridership considering demand elasticity with respect to travel time and fare. The proposed integrated service, consisting of local (e.g., all-stop) and express (e.g., stop-skipping) services, is optimized using a genetic algorithm (GA) subject to minimum service frequency and fleet size constraints. A numerical analysis is conducted under various operation scenarios based on a real-world bus route in Chengdu, China. The results suggest that the optimized integrated service may increase the ridership. The sensitivity analysis is conducted, and the impacts of model parameters on decision variables to the ridership are explored.
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Data Availability Statement
All data, models, or code generated or used during the study are confidential in nature and may only be provided with restrictions (e.g., potential demand data). The supporting data have not been made available due to confidentiality agreements with research collaborators, which can only be made available to bona fide researchers subject to a nondisclosure agreement.
Acknowledgments
This study was financially supported by National Engineering Laboratory of Integrated Transportation Big Data Application Technology (Grant No. CTBDAT201910), Science and Technology Department of Sichuan Province (Grant No. 2019JDTD0002), and Sichuan Transportation Science and Technology Program (Grant No. 2020-D-03) in China. The authors are grateful to anonymous reviewers for providing helpful suggestions for the study.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 147 • Issue 4 • April 2021
Copyright
© 2021 American Society of Civil Engineers.
History
Received: Aug 3, 2020
Accepted: Nov 30, 2020
Published online: Feb 11, 2021
Published in print: Apr 1, 2021
Discussion open until: Jul 11, 2021
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