We consider the necessary redistribution of bicycles in public bicycle sharing systems in order to avoid rental stations to run empty or entirely full. For this purpose we propose a general Variable Neighborhood Search (VNS) with an embedded Variable Neighborhood Descent (VND) that exploits a series of neighborhood structures. While this metaheuristic generates candidate routes for vehicles to visit unbalanced rental stations, the numbers of bikes to be loaded or unloaded at each stop are efficiently derived by one of three alternative methods based on a greedy heuristic, a maximum flow calculation, and linear programming, respectively. Tests are performed on instances derived from real-world data and indicate that the VNS based on a greedy heuristic represents the best compromise for practice. In general the VNS yields good solutions and scales much better to larger instances than two mixed integer programming approaches.
- Mixed Integer Programming
- Variable Neighborhood Search
- Vehicle Rout Problem
- Greedy Heuristic
- Tour Length
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This work is supported by the Austrian Research Promotion Agency (FFG), contract 831740.
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Rainer-Harbach, M., Papazek, P., Hu, B., Raidl, G.R. (2013). Balancing Bicycle Sharing Systems: A Variable Neighborhood Search Approach. In: Middendorf, M., Blum, C. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2013. Lecture Notes in Computer Science, vol 7832. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37198-1_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37197-4
Online ISBN: 978-3-642-37198-1