Balancing Bicycle Sharing Systems: An Analysis of Path Relinking and Recombination within a GRASP Hybrid

  • Petrina Papazek
  • Christian Kloimüllner
  • Bin Hu
  • Günther R. Raidl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8672)

Abstract

In bike sharing systems, a vehicle fleet rebalances the system by continuously moving bikes among stations in order to avoid rental stations to run entirely empty or full. We address the static problem variant assuming initial fill levels for each station and seek vehicle tours with corresponding loading instructions to reach given target fill levels as far as possible. Our primary objective is to minimize the absolute deviation between target and final fill levels for all rental stations. Building upon a previously suggested GRASP hybrid, we investigate different approaches for hybridizing them with Path Relinking (PR) and simpler recombination operators. Computational tests on benchmark instances derived from a real world scenario in Vienna give insight on the impacts of the PR and recombination techniques and manifest that certain PR extension improve the results significantly. Ultimately, a hybrid exclusively searching a partial PR path in the neighborhood of the guiding solutions turns out to be most fruitful.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    DeMaio, P.: Bike-sharing: History, impacts, models of provision, and future. Public Transportation 12(4), 41–56 (2009)MathSciNetGoogle Scholar
  2. 2.
    Rainer-Harbach, M., Papazek, P., Hu, B., Raidl, G.R.: Balancing bicycle sharing systems: A variable neighborhood search approach. In: Middendorf, M., Blum, C. (eds.) EvoCOP 2013. LNCS, vol. 7832, pp. 121–132. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  3. 3.
    Chemla, D., Meunier, F., Calvo, R.W.: Bike sharing systems: Solving the static rebalancing problem. Discrete Optimization 10(2), 120–146 (2013)MathSciNetCrossRefMATHGoogle Scholar
  4. 4.
    Raviv, T., Tzur, M., Forma, I.A.: Static repositioning in a bike-sharing system: models and solution approaches. EURO Journal on Transp. and Log., 1–43 (2013)Google Scholar
  5. 5.
    Benchimol, M., Benchimol, P., Chappert, B., De la Taille, A., Laroche, F., Meunier, F., Robinet, L.: Balancing the stations of a self service bike hire system. RAIRO – Operations Research 45(1), 37–61 (2011)CrossRefMATHGoogle Scholar
  6. 6.
    Schuijbroek, J., Hampshire, R., van Hoeve, W.J.: Inventory Rebalancing and Vehicle Routing in Bike Sharing Systems. Technical Report 2013-E1, Tepper School of Business, Carnegie Mellon University (2013)Google Scholar
  7. 7.
    Papazek, P., Raidl, G.R., Rainer-Harbach, M., Hu, B.: A PILOT/VND/GRASP hybrid for the static balancing of public bicycle sharing systems. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds.) EUROCAST. LNCS, vol. 8111, pp. 372–379. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  8. 8.
    Rainer-Harbach, M., Papazek, P., Hu, B., Raidl, G.R.: PILOT, GRASP, and VNS approaches for the static balancing of bicycle sharing systems. Journal of Global Optimization (2013), doi:10.1007/s10898-014-0147-5Google Scholar
  9. 9.
    Di Gaspero, L., Rendl, A., Urli, T.: A hybrid ACO+CP for balancing bicycle sharing systems. In: Blesa, M.J., Blum, C., Festa, P., Roli, A., Sampels, M. (eds.) HM 2013. LNCS, vol. 7919, pp. 198–212. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  10. 10.
    Di Gaspero, L., Rendl, A., Urli, T.: Constraint-based approaches for balancing bike sharing systems. In: Schulte, C. (ed.) CP 2013. LNCS, vol. 8124, pp. 758–773. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  11. 11.
    Contardo, C., Morency, C., Rousseau, L.M.: Balancing a dynamic public bike-sharing system. Technical Report CIRRELT-2012-09, Montreal, Canada (2012)Google Scholar
  12. 12.
    Kloimüllner, C., Papazek, P., Hu, B., Raidl, G.R.: Balancing bicycle sharing systems: An approach for the dynamic case. In: Evolutionary Computation in Combinatorial Optimization, 12 p. (to appear, 2014)Google Scholar
  13. 13.
    Lin, J.R., Yang, T.H., Chang, Y.C.: A hub location inventory model for bicycle sharing system design: Formulation and solution. Computers & Industrial Engineering 65(1), 77–86 (2013)CrossRefGoogle Scholar
  14. 14.
    Nair, R., Miller-Hooks, E., Hampshire, R.C., Bušić, A.: Large-scale vehicle sharing systems: Analysis of Vélib’. Int. Journal of Sustain. Transp. 7(1), 85–106 (2013)CrossRefGoogle Scholar
  15. 15.
    Voß, S., Fink, A., Duin, C.: Looking ahead with the PILOT method. Annals of Operations Research 136, 285–302 (2005)MathSciNetCrossRefMATHGoogle Scholar
  16. 16.
    Mladenović, N., Hansen, P.: Variable neighborhood search. Computers and Operations Research 24(11), 1097–1100 (1997)MathSciNetCrossRefMATHGoogle Scholar
  17. 17.
    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
  18. 18.
    Glover, F., Laguna, M., Marti, R.: Fundamentals of scatter search and path relinking. Control and Cybernetics 29(3), 653–684 (2000)MathSciNetMATHGoogle Scholar
  19. 19.
    Ho, S.C., Grendreau, M.: Path relinking for the vehicle routing problem. Heuristics 12(1-2), 55–72 (2006)CrossRefMATHGoogle Scholar
  20. 20.
    Rahimi-Vahed, A., Crainic, T., Gendreau, M., Rei, W.: A path relinking algorithm for a multi-depot periodic vehicle routing problem. Heuristics 19(3), 497–524 (2013)CrossRefGoogle Scholar
  21. 21.
    Festa, P., Resende, M.G.C.: Hybridizations of GRASP with path-relinking. In: Talbi, E.-G. (ed.) Hybrid Metaheuristics. SCI, vol. 434, pp. 139–159. Springer, Heidelberg (2013)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Petrina Papazek
    • 1
  • Christian Kloimüllner
    • 1
  • Bin Hu
    • 1
  • Günther R. Raidl
    • 1
  1. 1.Institute of Computer Graphics and AlgorithmsVienna University of TechnologyViennaAustria

Personalised recommendations