Tabu Search Hybridized with Multiple Neighborhood Structures for the Frequency Assignment Problem

  • Khaled AlrajhiEmail author
  • Jonathan Thompson
  • Wasin Padungwech
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9668)


This study proposes a tabu search hybridized with multiple neighborhood structures to solve a variant of the frequency assignment problem known as the minimum order frequency assignment problem. This problem involves assigning frequencies to a set of requests while minimizing the number of frequencies used. Several novel and existing techniques are used to improve the efficiency of this algorithm. This includes a novel technique that aims to determine a lower bound on the number of frequencies required from each domain for a feasible solution to exist, based on the underlying graph coloring model. These lower bounds ensure that the search focuses on parts of the solution space that are likely to contain feasible solutions. Our tabu search algorithm was tested on real and randomly generated benchmark datasets of the static problem and achieved competitive results.


  1. 1.
    Metzger, B.H.: Spectrum management technique presented at 38th national orsa meeting. Detroit, MI (Fall 1970) (1970)Google Scholar
  2. 2.
    Garey, M.R., Johnson, D.S.: A Guide to the Theory of NP-Completeness. WH Freemann, New York (1979)zbMATHGoogle Scholar
  3. 3.
    Kapsalis, A., Chardaire, P., Rayward-Smith, V.J., Smith, G.D.: The radio link frequency assignment problem: a case study using genetic algorithms. In: Fogarty, T.C. (ed.) AISB-WS 1995. LNCS, vol. 993, pp. 117–131. Springer, Heidelberg (1995)CrossRefGoogle Scholar
  4. 4.
    Crisan, C., Mühlenbein, H.: The frequency assignment problem: a look at the performance of evolutionary search. In: Hao, J.-K., Lutton, E., Ronald, E., Schoenauer, M., Snyers, D. (eds.) AE 1997. LNCS, vol. 1363, pp. 263–273. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  5. 5.
    Parsapoor, M., Bilstrup, U.: Ant colony optimization for channel assignment problem in a clustered mobile ad hoc network. In: Tan, Y., Shi, Y., Mo, H. (eds.) ICSI 2013, Part I. LNCS, vol. 7928, pp. 314–322. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  6. 6.
    Tiourine, S.R., Hurkens, C.A.J., Lenstra, J.K.: Local search algorithms for the radio link frequency assignment problem. Telecommun. Syst. 13(2–4), 293–314 (2000)CrossRefzbMATHGoogle Scholar
  7. 7.
    Bouju, A., Boyce, J.F., Dimitropoulos, C.H.D., Vom Scheidt, G., Taylor, J.G.: Tabu search for the radio links frequency assignment problem. Applied Decision Technologies (ADT-95) (London) (1995)Google Scholar
  8. 8.
    Hao, J.-K., Dorne, R., Galinier, P.: Tabu search for frequency assignment in mobile radio networks. J. Heuristics 4(1), 47–62 (1998)CrossRefzbMATHGoogle Scholar
  9. 9.
    Bouju, A., Boyce, J.F., Dimitropoulos, C.H.D., Vom Scheidt, G., Taylor, J.G., Likas, A., Papageorgiou, G., Stafylopatis, A.: Intelligent search for the radio link frequency assignment problem. In: Proceedings of the International Conference on Digital Signal Processing, Cyprus (1995)Google Scholar
  10. 10.
    Glover, F., Laguna, M.: Tabu search applications. In: Glover, F., Laguna, M. (eds.) Tabu Search, pp. 267–303. Springer, Heidelberg (1997)CrossRefGoogle Scholar
  11. 11.
    Mladenović, N., Hansen, P.: Variable neighborhood search. Comput. Oper. Res. 24(11), 1097–1100 (1997)MathSciNetCrossRefzbMATHGoogle Scholar
  12. 12.
    Hale, W.K.: Frequency assignment: theory and applications. Proc. IEEE 68(12), 1497–1514 (1980)CrossRefGoogle Scholar
  13. 13.
    Dorne, R., Hao, J.-K.: Constraint handling in evolutionary search: a case study of the frequency assignment. In: Ebeling, W., Rechenberg, I., Voigt, H.-M., Schwefel, H.-P. (eds.) PPSN 1996. LNCS, vol. 1141, pp. 801–810. Springer, Heidelberg (1996)CrossRefGoogle Scholar
  14. 14.
    Hao, J.-K., Perrier, L.: Tabu search for the frequency assignment problem in cellular radio networks. Technical report LGI2P, EMA-EERIE, Parc Scientifique Georges Besse, Nimes, France (1999)Google Scholar
  15. 15.
    Dowsland, K.A., Thompson, J.M.: An improved ant colony optimisation heuristic for graph colouring. Discrete Appl. Math. 156(3), 313–324 (2008)MathSciNetCrossRefzbMATHGoogle Scholar
  16. 16.
    Hertz, A., de Werra, D.: Using tabu search techniques for graph coloring. Computing 39(4), 345–351 (1987)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Khaled Alrajhi
    • 1
    Email author
  • Jonathan Thompson
    • 1
  • Wasin Padungwech
    • 1
  1. 1.School of MathematicsCardiff UniversityCardiffUK

Personalised recommendations