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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)

Abstract

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.

Keywords

Travel Salesman Problem Combinatorial Optimization Problem Pheromone Trail Operational Research Society Generalize Assignment Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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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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