Analysis and Optimization of a Bike-sharing System in Singapore

Cherlene Kuah Xuan Lin

Abstract

This project aims to provide insights and recommendations on optimizing bike-sharing services in Singapore. The project analyzed historical data on the usage of bike-sharing services, identified demand patterns and trends and established suitable model parameters for forecasting.

The project suggests using demand forecasting models to predict future usage patterns and adjust bike availability accordingly to improve service quality. It also recommends implementing rebalancing strategies to redistribute bikes across stations to ensure adequate supply during peak demand periods. A vehicle routing problem is formulated and solved to output rebalancing strategies to be communicated and executed by drivers.

Moreover, the project recommends investing in technology to enable real-time bike availability and usage monitoring. These monitoring tools allow operators to respond quickly to changes in demand and take proactive steps to rebalance bikes across stations.

The project highlights the importance of demand forecasting and rebalancing in optimizing bike-sharing services. With accurate demand prediction and effective relocation strategies, operators can improve service quality, increase customer satisfaction, and reduce operational costs.