Proactive vehicle routing with inferred demand to solve the bikesharing rebalancing problem

Robert Regue and Will Recker

Transportation Research Part E: Logistics and Transportation Review, 2014, vol. 72, issue C, 192-209

Abstract: Bikesharing suffers from the effects of fluctuating demand that leads to system inefficiencies. We propose a framework to solve the dynamic bikesharing repositioning problem based on four core models: a demand forecasting model, a station inventory model, a redistribution needs model, and a vehicle-routing model. The approach is proactive instead of reactive, as bike repositioning occurs before inefficiencies are observed. The framework is tested using data from the Hubway Bikesharing system. Simulation results indicate that system performance improvements of 7% are achieved reducing the number of empty and full events by 57% and 76%, respectively, during PM peaks.

Keywords: Bikesharing; Dynamic rebalancing problem; Proactive vehicle routing; Gradient boosting; Simulation (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (36)

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DOI: 10.1016/j.tre.2014.10.005

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