Multi-Objective Micro-Genetic Algorithm for Multicast Routing

멀티캐스트 라우팅을 위한 다목적 마이크로-유전자 알고리즘

  • Jun, Sung-Hwa (Department of Computer Engineering, KyungHee University) ;
  • Han, Chi-Geun (Department of Computer Engineering, KyungHee University)
  • 전성화 (경희대학교 컴퓨터공학과) ;
  • 한치근 (경희대학교 컴퓨터공학과)
  • Received : 20060700
  • Accepted : 20070700
  • Published : 2007.12.31

Abstract

The multicast routing problem lies in the composition of a multicast routing tree including a source node and multiple destinations. There is a trade-off relationship between cost and delay, and the multicast routing problem of optimizing these two conditions at the same time is a difficult problem to solve and it belongs to a multi-objective optimization problem (MOOP). A multi-objective genetic algorithm (MOGA) is efficient to solve MOOP. A micro-genetic algorithm(${\mu}GA$) is a genetic algorithm with a very small population and a reinitialization process, and it is faster than a simple genetic algorithm (SGA). We propose a multi-objective micro-genetic algorithm (MO${\mu}GA$) that combines a MOGA and a ${\mu}GA$ to find optimal solutions (Pareto optimal solutions) of multicast routing problems. Computational results of a MO${\mu}GA$ show fast convergence and give better solutions for the same amount of computation than a MOGA.

Keywords

References

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