# A simulation framework for the design of a station-based bike sharing system

arXiv: https://arxiv.org/abs/2106.10443 · HTML: https://mlsanity.com/paper/2106.10443/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jun 2021.

## Built on by (most cited first, 1 of 1)

- [The impact of machine learning forecasting on strategic decision-making for Bike Sharing Systems](https://mlsanity.com/paper/2603.14901/) (2026)

## Abstract (arXiv)

Many cities and towns offer to citizens a Bike-Sharing System (BSS). When a company starts the service, multiple decisions have to be taken at strategic, tactical, and operational level. When the service is in place, it is often necessary to adapt these decisions to changed conditions. In this paper, starting from the experience gained in the real-case of Bicimia in Brescia, Italy, we present a simulation framework to support decisions in the design or revision of a BSS, including the shifts of the operators, the number of vehicles and their capacity, the sizing of the stations, and the sizing of the fleet of bikes.