Balancing Bicycle Sharing Systems: A Variable Neighborhood Search Approach
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.
KeywordsMixed Integer Programming Variable Neighborhood Search Vehicle Rout Problem Greedy Heuristic Tour Length
Unable to display preview. Download preview PDF.
- 1.Chemla, D., Meunier, F., Calvo, R.W.: Bike sharing systems: Solving the static rebalancing problem. To appear in Discrete Optimization (2012)Google Scholar
- 2.Raviv, T., Tzur, M., Forma, I.A.: Static Repositioning in a Bike-Sharing System: Models and Solution Approaches. To appear in EURO Journal on Transportation and Logistics (2012)Google Scholar
- 4.Contardo, C., Morency, C., Rousseau, L.M.: Balancing a Dynamic Public Bike-Sharing System. Technical Report CIRRELT-2012-09, CIRRELT, Montreal, Canada (2012), submitted to Transportation ScienceGoogle Scholar
- 7.Pirkwieser, S., Raidl, G.R.: A variable neighborhood search for the periodic vehicle routing problem with time windows. In: Prodhon, C., et al. (eds.) Proceedings of the 9th EU/MEeting on Metaheuristics for Logistics and Vehicle Routing, Troyes, France (2008)Google Scholar
- 8.Resende, M., Ribeiro, C.: Greedy randomized adaptive search procedures. In: Glover, F., Kochenberger, G. (eds.) Handbook of Metaheuristics, pp. 219–249. Kluwer Academic Publishers (2003)Google Scholar