Abstract
Shared bicycles have become an important mode of urban slow traffic, and the operation and management of shared bicycles have attracted more and more attention. In order to alleviate the shortage of supply during peak period and accelerate the turnover rate during flat peak period, this paper proposes a differentiated pricing strategy of shared bicycles. By establishing a bilevel programming model of shared bicycles fare and using a particle swarm optimization-based global pricing model solution algorithm, the purpose of minimizing the generalized travel cost of travelers and maximizing the economic benefits of shared bicycles enterprises are achieved. Based on the actual traffic situation in Beijing, the model parameters are calibrated to verify the validity of the model and the algorithm. The proposed model can provide a reference for the pricing strategy of shared bicycles and provide a scientific basis for the operation and management of shared bicycles enterprises.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IOP Conference Series: Materials Science and Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
