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Satellite Customer Assignment: A Comparative Study of Genetic Algorithm and Ant Colony Optimization
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  • Satellite Customer Assignment: A Comparative Study of Genetic Algorithm and Ant Colony Optimization
  • Satellite Customer Assignment: A Comparative Study of Genetic Algorithm and Ant Colony Optimization
저자명
Kim. Sung-Soo,Kim. Hyoung-Joong,Mani. V.
간행물명
Journal of ubiquitous convergence technology
권/호정보
2008년|2권 1호|pp.40-50 (11 pages)
발행정보
대한전자공학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

The problem of assigning customers to satellite channels is a difficult combinatorial optimization problem and is NP-complete. For this combinatorial optimization problem, standard optimization methods take a large computation time and so genetic algorithms (GA) and ant colony optimization (ACO) can be used to obtain the best and/or optimal assignment of customers to satellite channels. In this paper, we present a comparative study of GA and ACO to this problem. Various issues related to genetic algorithms approach to this problem, such as solution representation, selection methods, genetic operators and repair of invalid solutions are presented. We also discuss an ACO for this problem. In ACO methodology, three strategies, ACO with only ranking, ACO with only max-min ant system (MMAS), and ACO with both ranking and MMAS, are considered. A comparison of these two approaches (i,e., GA and ACO) with the standard optimization method is presented to show the advantages of these approaches in terms of computation time.