Service Network Design of Bike Sharing Systems with Resource Constraints
Station-based bike sharing systems provide an inexpensive and flexible supplement to public transportation systems. However, due to spatial and temporal demand variation, stations tend to run full or empty over the course of a day. In order to establish a high service level, that is, a high percentage of users being able to perform their desired trips, it is therefore necessary to redistribute bikes among stations to ensure suitable time-of-day fill levels. As available resources are scarce, the tactical planning level aims to determine efficient master tours periodically executed by redistribution vehicles. We present a service network design formulation for the bike sharing redistribution problem taking into account trip-based user demand and explicitly considering service times for bike pick-up and delivery. We solve the problem using a two-stage MILP-based heuristic and present computational results for small real-world instances. In addition, we evaluate the performance of the master tours for multiple demand scenarios.
KeywordsBike sharing systems Bike redistribution Tactical planning Service network design Master tours
This research has been supported by the German Research Foundation (DFG) through the Research Training Group SocialCars (GRK 1931). The focus of the SocialCars Research Training Group is on significantly improving the city‘s future road traffic, through cooperative approaches. This support is gratefully acknowledged.
Partial funding for this project comes from the Discovery Grant and the Discovery Accelerator Supplements Programs of the Natural Science and Engineering Research Council of Canada, and the Strategic Clusters program of the Fonds québécois de la recherche sur la nature et les technologies. The authors thank the two institutions for supporting this research.
- 3.Vogel, P., Neumann-Saavedra, B.A., Mattfeld, D.C.: A hybrid metaheuristic to solve the resource allocation problem in bike sharing systems. In: Blesa, M.J., Blum, C., Voß, S. (eds.) HM 2014. LNCS, vol. 8457, pp. 16–29. Springer, Heidelberg (2014)Google Scholar
- 4.Büttner, J., Petersen, T.: Optimising Bike Sharing in European Cities-A Handbook. Intelligent Energy Europe, European Commission (2011)Google Scholar
- 6.Brinkmann, J., Ulmer, M. W., Mattfeld, D.C.: Inventory routing for bike sharing systems. Working Paper, 12 January 2015Google Scholar
- 12.Contardo, C., Morency, C., Rousseau, L.M.: Balancing a dynamic public bike-sharing system, vol. 4. CIRRELT (2012)Google Scholar
- 13.Kloimüllner, C., Papazek, P., Hu, B., Raidl, G.R.: Balancing bicycle sharing systems: an approach for the dynamic case. In: Blum, C., Ochoa, G. (eds.) EvoCOP 2014. LNCS, vol. 8600, pp. 73–84. Springer, Heidelberg (2014)Google Scholar