Balancing bike sharing systems is an increasingly important problem, because of the rising popularity of this mean of transportation. Bike sharing systems need to be balanced so that bikes (and empty slots for returning bikes) are available to the customers, thus ensuring an adequate level of service. In this paper, we tackle the problem of balancing a real-world bike sharing system (BBSP) by means of a hybrid metaheuristic method. Our main contributions are: (i) a new Constraint Programming (CP) formulation for the problem, and (ii) a novel hybrid approach which combines CP techniques with Ant Colony Optimization (ACO). We validate our approach against real world instances from the Vienna Citybike system.
