A Comparison of Acceptance Criteria for the Daily Car-Pooling Problem

  • Jerry Swan
  • John Drake
  • Ender Özcan
  • James Goulding
  • John Woodward
Conference paper

Abstract

Previous work on the Daily Car-Pooling problem includes an algorithm that consists of greedy assignment alternating with random perturbation. In this study, we examine the effect of varying the move acceptance policy, specifically Late-acceptance criteria with and without reheating. Late acceptance-based move acceptance criteria were chosen because there is strong empirical evidence in the literature indicating their superiority. Late-acceptance compares the objective values of the current solution with one which was obtained at a fixed number of steps prior to the current step during the search process in order to make an acceptance decision. We observe that the Late-acceptance criteria also achieve superior results in over 75 % of cases for the Daily Car-Pooling problem, the majority of these results being statistically significant.

References

  1. 1.
    Baldacci, R., Maniezzo, V., Mingozzi, A.: An exact method for the car pooling problem based on Lagrangean column generation. Oper. Res. 52(3), 422–439 (2004)Google Scholar
  2. 2.
    Burke, E.K., Bykov, Y.: A late acceptance strategy in Hill-Climbing for exam timetabling problems. In: PATAT ’08 (2008)Google Scholar
  3. 3.
    Calvo, R.W., De Luigi, F., Haastrup, P., Maniezzo, V.: A distributed geographic information system for the daily car pooling problem. Comput. Oper. Res. 31(13), 2263–2278 (2004)Google Scholar
  4. 4.
    Christofides, N., Eilon, S.: An algorithm for the vehicle dispatching problem. Oper. Res. Q. 20(3), 309–318 (1969)Google Scholar
  5. 5.
    Christofides, N., Mingozzi, A., Toth, P.: The vehicle routing problem. In: Christofides, N., Mingozzi, A., Toth, P., Sandi, C. (eds.) Combinatorial Optimization, pp. 315–338. Wiley, Chichester (1979)Google Scholar
  6. 6.
    Cordeau, J.F., Laporte, G.: The dial-a-ride problem (darp): variants, modeling issues and algorithms. 4OR 1, 89–101 (2003)Google Scholar
  7. 7.
    Fisher, M.L.: Optimal solution of vehicle routing problems using minimum K-trees. Oper. Res. 42(4), 626–642 (1994)MathSciNetMATHCrossRefGoogle Scholar
  8. 8.
    Maniezzo, V., Carbonaro, A., Hildmann, H.: An ANTS heuristic for the Long-Term Car-Pooling Problem. In: Onwuboulu, G., Babu, B. (eds.) New Optimization Techniques in Engineering. Springer, Heidelberg (2002)Google Scholar
  9. 9.
    Mulvey, J.M., Beck, M.P.: Solving capacitated clustering problems. Eur. J. Oper. Res. 18(3), 339–348 (1984)Google Scholar
  10. 10.
    Özcan, E., Bilgin, B., Korkmaz, E.E.: A comprehensive analysis of hyper-heuristics. Intell. Data Anal. 12(1), 3–23 (2008)Google Scholar
  11. 11.
    Özcan, E., Bykov, Y., Birben, M., Burke, E.K.: Examination timetabling using late acceptance hyper-heuristics. In: Proceedings of the Eleventh Conference on Congress on Evolutionary Computation (CEC’09), pp. 997–1004. IEEE Press, Piscataway, NJ, USA (2009)Google Scholar
  12. 12.
    Swan, J., Özcan, E., Kendall, G.: Hyperion—a recursive hyper-heuristic framework. In: Coello Coello, C.A. (ed.) 5th International Conference on Learning and Intelligent Optimization (LION 5), LNCS (2011)Google Scholar
  13. 13.
    Toth, P., Vigo, D.: An overview of vehicle routing problems. In: The vehicle routing problem, Society for Industrial and Applied Mathematics, pp. 1–26. Philadelphia, PA, USA (2001)Google Scholar
  14. 14.
    Verstichel, J., Berghe, G.V.: A late acceptance algorithm for the lock scheduling problem. In: Voss, S., Pahl, J., Schwarze, S. (eds.) Logistik Management, pp. 457–478. Physica-Verlag HD, Heidelberg (2009)Google Scholar

Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Jerry Swan
    • 1
  • John Drake
    • 1
  • Ender Özcan
    • 1
  • James Goulding
    • 2
  • John Woodward
    • 1
  1. 1.Automated Scheduling, Optimisation and Planning (ASAP) Research GroupNottinghamUK
  2. 2.School of Computer Science, Horizon Digital Economy Research InstituteUniversity of NottinghamNottinghamUK

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