Shared e-bike operational planning under different relocation schemes: A smart campus case

Abstract

Major urban centers are grappling with challenges related to urban mobility and elevated greenhouse gas emissions. Shared electric bicycles (e-bikes) present a potential solution to these issues. Nonetheless, many ventures of this nature have previously faltered due to high operational costs. This paper aims to assess the optimal decisions for a shared e-bike company serving a university community. To this end, we consider two relocation strategies: one led by the operator and another by the user. Additionally, we examine elements inherent to a smart campus, such as photovoltaic systems and advanced energy tariffs, like time-of-use and real-time tariffs. We modeled the optimization problem as a mixed-integer nonlinear program, further linearized to a mixed-integer linear program using the Big-M method. Our case study focuses on the academic community at Universidade Federal Fluminense in Niterói, Brazil. Findings suggest a trade-off between operator and user relocation tariffs. They also underscore an enhancement in meeting demand, from 51 % to 69 %, when both mechanisms are employed. Lastly, the smart campus influences the operator's decisions, highlighting the importance of considering the interplay between energy and rental tariffs during planning.

Keywords

• e-bike
• Relocation
• Smart campus
• Optimization