How to Choose Solutions for Local Search in Multiobjective Combinatorial Memetic Algorithms

@inproceedings{Ishibuchi2010HowTC,
  title={How to Choose Solutions for Local Search in Multiobjective Combinatorial Memetic Algorithms},
  author={Hisao Ishibuchi and Yasuhiro Hitotsuyanagi and Yoshihiko Wakamatsu and Yusuke Nojima},
  booktitle={PPSN},
  year={2010}
}
This paper demonstrates that the performance of multiobjective memetic algorithms (MOMAs) for combinatorial optimization strongly depends on the choice of solutions to which local search is applied. We first examine the effect of the tournament size to choose good solutions for local search on the performance of MOMAs. Next we examine the effectiveness of an idea of applying local search only to non-dominated solutions in the offspring population. We show that this idea has almost the same… CONTINUE READING
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A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II

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