Xiaoting Mo
ABSTRACT
We develop a Markovian queueing model to analyze the steady behavior of a dockless bike-sharing system and adopt probabilities of having a certain number of bikes at each node as the basis of our study. Probabilities, as well as other conditions of bikes and customers, help us obtain the average ratio of number of customers we serve successfully or customers we lose regrettably to customers' total demands for borrowing bikes. Considering the bike sharing rebalancing problem which happens frequently in real systems, we propose a closed-form approximation for calculating the total profits of the whole system efficiently and finding the optimal relocation frequency by maximizing profits, not just maximizing revenue or minimizing cost. The cost of customer churn derived from customers finding no bike available at some nodes is also included in the objective function. Multiple numerical experiments illustrate the relationship among maximum profit, optimal relocation frequency and some key parameters. Based on the results from analysis, we suggest to operators of dockless bike-sharing systems that they should consider the balance of demand at the design phase of a system and reduce relocation cost to an appropriate level. Our methods are applicable to systems with no size limitation.
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Index Terms
- Modeling and Optimizing Resource Sharing Systems: Application to Bike Sharing with Unequal Demands and Relocations Using Queueing Theory
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