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Two Look-Ahead Strategies for Local-Search Metaheuristics

  • David Meignan
  • Silvia Schwarze
  • Stefan Voß
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8426)

Abstract

The main principle of a look-ahead strategy is to inspect a few steps ahead before taking a decision on the direction to choose. We propose two original look-ahead strategies that differ in the object of inspection. The first method introduces a look-ahead mechanism at a superior level for selecting local-search operators. The second method uses a look-ahead strategy on a lower level in order to detect promising solutions for further improvement. The proposed approaches are implemented using a hyper-heuristic framework and tested against alternative methods. Furthermore, a more detailed investigation of the second method is added and gives insight on the influence of parameter values. The experiments reveal that the introduction of a simple look-ahead strategy into an iterated local-search procedure significantly improves the results over tested problem instances.

Keywords

Metaheuristic Hyper-heuristic Look-ahead Iterated local-search 

References

  1. 1.
    Bertsekas, D.P., Tsitsiklis, J.N., Wu, C.: Rollout algorithms for combinatorial optimization. J. Heuristics 3, 245–262 (1997)CrossRefzbMATHGoogle Scholar
  2. 2.
    Blum, C., Roli, A.: Metaheuristics in combinatorial optimization: overview and conceptual comparison. ACM Comput. Surv. 35(3), 268–308 (2003)CrossRefGoogle Scholar
  3. 3.
    Burke, E.K., Gendreau, M., Hyde, M., Kendall, G., McCollum, B., Ochoa, G., Parkes, A.J., Petrovic, S.: The cross-domain heuristic search challenge – an international research competition. In: Coello, C.A.C. (ed.) LION 5. LNCS, vol. 6683, pp. 631–634. Springer, Heidelberg (2011) CrossRefGoogle Scholar
  4. 4.
    Burke, E.K., Hyde, M., Kendall, G., Ochoa, G., Özcan, E., Woodward, J.R.: A classification of hyper-heuristic approaches. In: Gendreau, M., Potvin, J.-Y. (eds.) Handbook of Metaheuristics. International Series in Operations Research & Management Science, vol. 146, pp. 449–468. Springer, Heidelberg (2010) CrossRefGoogle Scholar
  5. 5.
    Duin, C., Voß, S.: The pilot method: a strategy for heuristic repetition with application to the Steiner problem in graphs. Networks 34, 181–191 (1999)CrossRefzbMATHMathSciNetGoogle Scholar
  6. 6.
    Frost, D., Dechter, R.: Look-ahead value ordering for constraint satisfaction problems. In: Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, pp. 572–578 (1995)Google Scholar
  7. 7.
    Hansen, P., Mladenović, N., Brimberg, J., Pérez, J.A.M.: Variable neighborhood search. In: Gendreau, M., Potvin, J.-Y. (eds.) Handbook of Metaheuristics. International Series in Operations Research & Management Science, vol. 146, pp. 61–86. Springer, New York (2010) CrossRefGoogle Scholar
  8. 8.
    Lourenço, H., Martin, O., Stützle, T.: Iterated local search. In: Glover, F., Kochenberger, G.A. (eds.) Handbook of Metaheuristics. International Series in Operations Research & Management Science, vol. 57, pp. 320–353. Springer, Heidelberg (2003)Google Scholar
  9. 9.
    Ochoa, G., et al.: HyFlex: a benchmark framework for cross-domain heuristic search. In: Hao, J.-K., Middendorf, M. (eds.) EvoCOP 2012. LNCS, vol. 7245, pp. 136–147. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  10. 10.
    Ochoa, G., Walker, J., Hyde, M., Curtois, T.: Adaptive evolutionary algorithms and extensions to the hyflex hyper-heuristic framework. In: Coello, C.A.C., Cutello, V., Deb, K., Forrest, S., Nicosia, G., Pavone, M. (eds.) PPSN 2012, Part II. LNCS, vol. 7492, pp. 418–427. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  11. 11.
    Schwarze, S., Voß, S.: Look ahead hyper heuristics. In: Fink, A., Geiger, M. (eds.) Proceedings of the 14th EU/ME Workshop, pp. 91–97 (2013)Google Scholar
  12. 12.
    Voß, S., Fink, A., Duin, C.: Looking ahead with the pilot method. Ann. Oper. Res. 136, 285–302 (2005)CrossRefzbMATHMathSciNetGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Mathematics and Computer ScienceUniversity of OsnabrückOsnabrückGermany
  2. 2.Institute of Information SystemsUniversity of HamburgHamburgGermany

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