Over the past few years, Bike-Sharing Systems (BSS) have been widely adopted, becoming a familiar part of the urban landscape. In practice, the stations where these shared bikes are parked are often strategically placed near public transportation (PT) stops to facilitate seamless connections between bike-sharing and public transit. Yet, the academic literature lacks decision-support models to determine station locations in mobility systems that integrate bike-sharing with public transportation. Therefore, this paper presents a novel optimization problem, and corresponding mathematical model, for deciding on station locations while specifically accounting for an existing PT network. A numerical study is presented to compare our integrated approach with a case in which bike-sharing station locations are chosen independently of the PT network. This provides insights into how the integration affects demand coverage and to what extent it enhances accessibility in urban areas.
Bayri et al. (2025) studied this question.