Title:

Real-Time Optimization of UNH Bike Share System

Bike availability is a key concern in bike share systems. Our project aims to provide the Sustainability Institute's Cat Trax Bike Share system with an effective algorithm for redistributing bikes. After defining a metric for demand, we propose a simple heuristic approach for addressing demand at bike stations. Simulation results indicate our heuristic performs consistently better than the status quo when configured properly. Tuning our heuristic with data from previous bike share seasons may significantly improve results, assuming demand is consistent between seasons. Additional data visualizations were generated to provide Cat Trax faculty with general insight into bike demand. Software will be officially implemented at the Sustainability Institute within the month. We hope to demonstrate the potential of data science applied to sustainability at UNH.

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