Sustainable micromobility in cities: Optimization of shared bicycles

• Detailed mixed-integer programming model for BSS operation optimization. • Algorithmic approach cuts complexity for 210+ station BSS problems. • Model combines different time intervals for demand and vehicle relocations. • Operators' work increases satisfied demand by 10 to 20% during the day on average. • Verification using real data from a commercial BSS in the Czech Republic. Ensuring mobility and transportation services is a key factor for economic growth today. Urban public transportation cannot fully meet individual needs, which led to the introduction of shared transportation options. These systems allow for more flexible mobility, but challenges are still associated with the efficiency of provided services. Tasks such as regular maintenance and relocation between stations are often carried out by workers’ experiences, leading to inefficient route planning and imbalanced stations. Analyzing the current bike-sharing operations and optimizing transport and management can contribute to more efficient worker routes and increase bike rentals. This research focuses on planning rebalancing and maintenance routes while considering various criteria. This approach makes it possible to prioritize different tasks or locations and uncertainties in demand. The main criterion is to ensure the sustainability and efficiency of the whole operation chain. The solution is obtained from a custom-designed algorithm explicitly tailored to this problem. The proposed approach should contribute to optimizing the daily routine of workers, ensuring greater availability of shared transportation options. The model and the corresponding algorithm have been verified using real data from a commercial bike-sharing system in one of the cities of the Czech Republic. The results demonstrate that operators contribute to approximately 10 to 20% of the satisfied demand.