Ant Colony Optimization for Satellite Customer Assignment

  • S. S. Kim
  • H. J. Kim
  • V. Mani
  • C. H. Kim
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4412)


This paper considers the meta-heuristic method of ant colony optimization to the problem of assigning customers to satellite channels. It is shown in an earlier study that finding an optimal allocation of customers to satellite channels is a difficult combinatorial optimization problem and is NP-complete. Hence, we propose an ant colony system (ACS) with strategies of ranking and Max-Min ant system (MMAS) for an effective search of the best/optimal assignment of customers to satellite channels under a dynamic environment. Our simulation results show that this methodology is successful in finding an assignment of customers to satellite channels. Three strategies, ACS with only ranking, ACS with only MMAS, and ACS with both ranking and MMAS are considered. A comparison of these strategies are presented to show the performance of each strategy.


Travel Salesman Problem Combinatorial Optimization Problem Pheromone Trail Operational Research Society Generalize Assignment Problem 
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  1. 1.
    Bonabeau, E., Dorigo, M., Theraulez, G.: Swarm Intelligence: From Natural to Artificial Intellience. Oxford University Press, New York (1999)Google Scholar
  2. 2.
    Bullnheimer, B., Hartl, R., Strauss, C.: An improved ant system algorithm for the vehicle routing problem. Annals of Operations Research 89, 319–328 (1999)zbMATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Cattrysse, D., Van Wassenhove, L.N.: A survey of algorithms for the generalized assignment problem. European Journal of Operational Research 60, 260–272 (1992)zbMATHCrossRefGoogle Scholar
  4. 4.
    Dell’Amico, M., Martello, S.: Open shop, satellite communication and a theorem by Egervary (1931). Operations Research Letters 18, 209–211 (1996)CrossRefMathSciNetGoogle Scholar
  5. 5.
    Dorigo, M., Di Caro, G., Gambardella, L.M.: Ant algorithms for discrete optimization. Artificial Life 5, 137–172 (1999)CrossRefGoogle Scholar
  6. 6.
    Dorigo, M., Maniezzo, V., Colorni, A.: The ant system: Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics B26, 29–41 (1996)Google Scholar
  7. 7.
    Dorigo, M., Stutzle, T.: The ant colony optimization metaheuristic: algorithms, applications, and advances. In: Glover, F., Kochenberger, G. (eds.) Handbook of Metaheuristics, pp. 251–258. Kluwer Academic Publishers, Norwell (2002)Google Scholar
  8. 8.
    Lee, H., Ahn, D.H., Kim, S.: Optimal routing in non-geostationary satellite ATM networks with intersatellite link capacity constraints. Journal of the Operational Research Society 54, 401–409 (2003)zbMATHCrossRefGoogle Scholar
  9. 9.
    Levine, J., Ducatelle, F.: Ant colony optimization and local search for bin packing and cutting stock problems. Journal of the Operational Research Society 55, 705–716 (2004)zbMATHCrossRefGoogle Scholar
  10. 10.
    Montgomery, D.C., Johnson, L.A.: Operations Research in Production Planning Scheduling and Inventory Control. John Wiley & Sons, Chichester (1974)Google Scholar
  11. 11.
    Prins, C.: An overview of scheduling problems arising in satellite communications. Journal of the Operational Research Society 45, 611–623 (1994)zbMATHCrossRefGoogle Scholar
  12. 12.
    Scott, C.H., Skelton, O.G., Rolland, E.: Tactical and strategic models for satellite customer assignment. Journal of the Operational Research Society 51, 61–71 (2000)zbMATHCrossRefGoogle Scholar
  13. 13.
    Stützle, T.: MAX-MIN Ant system for the quadratic assignment problem. Technical Report AIDA-97-4, FG Intellektik, TU Darmstadt, Germany (1997)Google Scholar
  14. 14.
    Tarasewich, P., McMullen, P.R.: Swarm intelligence: Power in numbers. Communications of the ACM 45, 62–67 (2002)CrossRefGoogle Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • S. S. Kim
    • 1
  • H. J. Kim
    • 2
  • V. Mani
    • 3
  • C. H. Kim
    • 4
  1. 1.Department of Industrial Engineering, Kangwon National University, Chunchon 200-701Korea
  2. 2.CIST, Korea University, Seoul 136-701Korea
  3. 3.Department of Aerospace Engineering, Indian Institute of Science, Bangalore, 560-012India
  4. 4.Ainsolution Co., SeoulKorea

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