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Algorithms for Radio Link Frequency Assignment: The Calma Project

Author

Listed:
  • Karen Aardal

    (Department of Mathematics, Utrecht University, Budapestlaan 6, 3584 CD Utrecht, The Netherlands)

  • Cor Hurkens

    (Department of Mathematics and Computer Science, Technische Universiteit Eindhoven, 5600 MB Eindhoven, The Netherlands)

  • Jan Karel Lenstra

    (Department of Mathematics and Computer Science, Technische Universiteit Eindhoven, 5600 MB Eindhoven, The Netherlands)

  • Sergey Tiourine

    (Department of Mathematics and Computer Science, Technische Universiteit Eindhoven, 5600 MB Eindhoven, The Netherlands)

Abstract

The radio link frequency assignment problem occurs when a network of radio links has to be established. Each link must be assigned an operating frequency from a given domain. The assignment has to satisfy certain restrictions so as to limit the interference between links. The number of frequencies used is to be minimized.Problems of this type were investigated within the CALMA project by a consortium consisting of research groups from Delft, Eindhoven, London, Maastricht, Norwich, and Toulouse. The participants developed optimization algorithms based on branch-and-cut and constraint satisfaction, and approximation techniques including a variety of local search methods, genetic algorithms, neural networks, and potential reduction. These algorithms were tested and compared on a set of real-life instances.

Suggested Citation

  • Karen Aardal & Cor Hurkens & Jan Karel Lenstra & Sergey Tiourine, 2002. "Algorithms for Radio Link Frequency Assignment: The Calma Project," Operations Research, INFORMS, vol. 50(6), pages 968-980, December.
    • Handle: RePEc:inm:oropre:v:50:y:2002:i:6:p:968-980
    DOI: 10.1287/opre.50.6.968.353
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    References listed on IDEAS

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    1. K. Aardal & C. P. M. van Hoesel, 1996. "Polyhedral techniques in combinatorial optimization I: Theory," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 50(1), pages 3-26, March.
    2. Peter J. M. van Laarhoven & Emile H. L. Aarts & Jan Karel Lenstra, 1992. "Job Shop Scheduling by Simulated Annealing," Operations Research, INFORMS, vol. 40(1), pages 113-125, February.
    3. Eugeniusz Nowicki & Czeslaw Smutnicki, 1996. "A Fast Taboo Search Algorithm for the Job Shop Problem," Management Science, INFORMS, vol. 42(6), pages 797-813, June.
    4. S. Lin & B. W. Kernighan, 1973. "An Effective Heuristic Algorithm for the Traveling-Salesman Problem," Operations Research, INFORMS, vol. 21(2), pages 498-516, April.
    5. K. Aardal & C. P. M. Van Hoesel, 1999. "Polyhedral techniques in combinatorial optimization II: applications and computations," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 53(2), pages 131-177, July.
    6. Koster, Arie & van Hoesel, C.P.M. & Kolen, A.W.J., 1999. "Solving frequency assignment problems via tree-decomposition," Research Memorandum 011, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    7. Fischetti, Matteo & Lepschy, Chiara & Minerva, Giuseppe & Romanin-Jacur, Giorgio & Toto, Ema, 2000. "Frequency assignment in mobile radio systems using branch-and-cut techniques," European Journal of Operational Research, Elsevier, vol. 123(2), pages 241-255, June.
    8. J. P. Warners, 1998. "A nonlinear approach to a class of combinatorial optimization problems," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 52(2), pages 162-184, June.
    9. Koster A.M.C.A. & Hoesel S.P.M. van & Kolen A.W.J., 1999. "Solving frequency assignment problems via tree-decomposition," Research Memorandum 036, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
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    Citations

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    Cited by:

    1. Kolen, A.W.J., 2006. "A genetic algorithm for the partial binary constraint satisfaction problem: an application to a frequency assignment problem," Research Memorandum 045, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    2. Karen Aardal & Stan Hoesel & Arie Koster & Carlo Mannino & Antonio Sassano, 2007. "Models and solution techniques for frequency assignment problems," Annals of Operations Research, Springer, vol. 153(1), pages 79-129, September.
    3. Dupont, Audrey & Linhares, Andréa Carneiro & Artigues, Christian & Feillet, Dominique & Michelon, Philippe & Vasquez, Michel, 2009. "The dynamic frequency assignment problem," European Journal of Operational Research, Elsevier, vol. 195(1), pages 75-88, May.

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