Local search for multiobjective function optimization: pareto descent method

@inproceedings{Harada2006LocalSF,
  title={Local search for multiobjective function optimization: pareto descent method},
  author={Ken Harada and Jun Sakuma and Shigenobu Kobayashi},
  booktitle={GECCO},
  year={2006}
}
Genetic Algorithm (GA) is known as a potent multiobjective optimization method, and the effectiveness of hybridizing it with local search (LS) has recently been reported in the literature. However, there is a relatively small number of studies on LS methods for multiobjective function optimization. Although each of the existing LS methods has some strong points, they have respective drawbacks such as high computational cost and inefficiency in improving objective functions. Hence, a more… CONTINUE READING
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