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Adaptive Tabu Tenure Computation in Local Search

  • Conference paper
Book cover Evolutionary Computation in Combinatorial Optimization (EvoCOP 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4972))

Abstract

Optimization methods based on complete neighborhood exploration such as Tabu Search are impractical against large neighborhood problems. Strategies of candidate list propose a solution to reduce the neighborhood exploration complexity. We propose in this paper a generic Tabu Search algorithm using adaptive candidate list strategy based on two alternate candidate lists. Each candidate list strategy corresponds to a given search phase: intensification or diversification. The optimization algorithm uses a Tabu list containing the variables causing loops. The paper proposes a classification of Tabu tenure managing in the literature and presents a new and original Tabu tenure adaptation mechanism. The generic method is tested on the k-coloring problem and compared with some best methods published in the literature. Obtained results show the competitiveness of the method.

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References

  1. Bachelet, V., Talbi, E.-G.: COSEARCH: a co-evolutionary metaheuristic. In: Proceedings of the Congress on Evolutionary Computation CEC 2000, pp. 1550–1557 (2000)

    Google Scholar 

  2. Battiti, R., Tecchiolli, G.: The reactive Tabu search. ORSA Journal on Computing 6(2), 126–140 (1994)

    MATH  Google Scholar 

  3. Battiti, R.V.J., Rayward-Smith, I.O., Smith, G. (eds.): Reactive Search: Toward Self-Tuning Heuristics, pp. 61–83. John Wiley and Sons Ltd, Chichester (1996)

    Google Scholar 

  4. Blöchliger, I.: Suboptimal colorings and solution of large chromatic scheduling problems, Ph.D. thesis, Mathematics Department, Ecole polytechnique federale de Lausanne, Lausanne, Suisse, 20056

    Google Scholar 

  5. Chiarandini, M., Dumitrescu, I., Stutzle, T.: Stochastic Local Search for the Graph Colouring Problem, Technical Report AIDA-05-03 (2005)

    Google Scholar 

  6. Devarenne, I., Mabed, H., Caminada, A.: Intelligent neighborhood exploration in local search heuristics. In: 18th IEEE International Conference on Tools with Artificial Intelligence, Washington D.C. USA (2006)

    Google Scholar 

  7. Devarenne, I., Mabed, H., Caminada, A.: Self-adaptive Neighborhood Exploration Parameters in Local Search. In: 7th EU/MEeting on Adaptive, Self-Adaptive, and Multi-Level Metaheuristics, University of Málaga, Spain (2006)

    Google Scholar 

  8. Di Gaspero, L., Schaerf, A.: A Tabu Search Approach to the Traveling Tournament Problem. In: MIC 2005: The 6th Metaheuristics International Conference, Vienna, Austria (2005)

    Google Scholar 

  9. Dorne, R., Hao, J.K.: Tabu Search for graph coloring, T-coloring and Set T-colorings. In: Osman, I.H., et al. (eds.) Metaheuristics 1998: Theory and Applications, ch. 3, Kluver Academic Publishers (1998)

    Google Scholar 

  10. Dupont, A.: Étude d’une métaheuristique hybride pour l’affectation de fréquences dans les réseaux tactiques évolutifs, PhD thesis, Univ. Montpellier II, France (2005)

    Google Scholar 

  11. Galinier, P., Hao, J.-K.: Hybrid Evolutionary Algorithms for Graph Coloring. Journal of Combinatorial Optimization 3, 379–397 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  12. Galinier, P., Hertz, A., Zufferey, N.: An Adaptive Memory Algorithm for the k-colouring problem. Les Cahiers du GERAD G-2003-35 (2004)

    Google Scholar 

  13. Glover, F.: Tabu Search - Part I. ORSA Journal on Computing 1(3), 190–206 (1989)

    MATH  Google Scholar 

  14. Glover, F.: Tabu Search - Part II. ORSA Journal on Computing 2(1), 4–32 (1990)

    MATH  Google Scholar 

  15. Hansen, P., Jaumard, B.: Algorithms for the maximum satisfiability problem. Computing 4(44), 279–303 (1990)

    Article  MathSciNet  Google Scholar 

  16. Hao, J.-K., Galinier, P.: Tabu search for maximal constraint satisfaction problems. In: Smolka, G. (ed.) CP 1997. LNCS, vol. 1330, pp. 196–208. Springer, Heidelberg (1997)

    Google Scholar 

  17. Hao, J.K., Dorne, R., Galinier, P.: Tabu search for frequency assignment in mobile radio networks. Journal of Heuristics 4(1), 47–62 (1998)

    Article  MATH  Google Scholar 

  18. Leighton, F.: A graph coloring algorithm for large scheduling problems. Journal of research of the national bureau of standards, 489–505 (1979)

    Google Scholar 

  19. Mabed, H., Devarenne, I., Caminada, A., Defaix, T.: Frequency Planning for Military Slow Frequency Hopping System. In: International Network Optimization Conference 2007, Spa, Belgium (2007)

    Google Scholar 

  20. Montemanni, R., Smith, D.H.: A Tabu search Algorithm with a dynamic Tabu list for the Frequency Assignment Problem, Technical Report, University of Glamorgan (2001)

    Google Scholar 

  21. Taillard, E.: Robust taboo search for the quadratic assignment problem. Parallel Computing 17, 443–455 (1991)

    Article  MathSciNet  Google Scholar 

  22. Neveu, B., Trombettoni, G., Glover, F.: A Candidate List Strategy with a Simple Diversification Device. In: Wallace, M. (ed.) CP 2004. LNCS, vol. 3258, pp. 423–437. Springer, Heidelberg (2004)

    Google Scholar 

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Jano van Hemert Carlos Cotta

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Devarenne, I., Mabed, H., Caminada, A. (2008). Adaptive Tabu Tenure Computation in Local Search. In: van Hemert, J., Cotta, C. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2008. Lecture Notes in Computer Science, vol 4972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78604-7_1

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  • DOI: https://doi.org/10.1007/978-3-540-78604-7_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-78603-0

  • Online ISBN: 978-3-540-78604-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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