Designing Dynamic Pricing for Bike-sharing Systems via Differentiable Agent-based Simulation
A differentiable agent-based simulation was developed to rapidly design dynamic pricing for bike-sharing systems. This method successfully balances bicycle inventory across stations by accounting for user heterogeneity and probabilistic choices, achieving accurate solutions with significant speed improvements over conventional methods.