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An association rule based framework for dynamic systems rebalancing: an application to bike sharing.
Rel. Paolo Garza, Sara Comai. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2020
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Abstract
Bike sharing systems are spreading throughout the world, being used by more and more people every day. Anyway, a higher diffusion means more bikes to manage and reorganise among bike sharing stations to guarantee a good quality of the service. Up to today, it does not exist a universally accepted algorithm to rebalance the distribution of bikes over a dock-based bike sharing system. From an extensive review of the current state of the art, it appears that, although bike sharing is a very active research field, there are few papers about dynamic rebalancing algorithms and all the existing ones are based on mathematical models of bike sharing stations.
This thesis presents a completely data-driven based framework to solve the dynamic rebalancing problem of a bike sharing dock-based system and its application on Barcelona’s bike sharing system
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