Optimal bike fleet management by smart relocation methods: Combining an operator-based with an user-based relocation strategy

Abstract

Based on an empirical data analysis, a simulation was built up in order to forecast the upcoming demand for an urban Bike Sharing System (BSS). To satisfy this demand, a relocation strategy is applied to rebalance the fleet of the BSS. In case of moderate imbalances, a pricing model incents users to ride bikes from “bad” to “good” spots. This saves operator's cost as no further relocation trips by trucks are generated. If the imbalances are severe though, the user-based method is not sufficient and the operator needs to intervene supplementary. Therefore, the relocation model provides an optimal strategy to combine both methods.