Constructing low star discrepancy point sets with genetic algorithms

@inproceedings{Doerr2013ConstructingLS,
  title={Constructing low star discrepancy point sets with genetic algorithms},
  author={Carola Doerr and François-Michel De Rainville},
  booktitle={GECCO '13},
  year={2013}
}
  • Carola Doerr, François-Michel De Rainville
  • Published in GECCO '13 2013
  • Computer Science
  • Geometric discrepancies are standard measures to quantify the irregularity of distributions. They are an important notion in numerical integration. One of the most important discrepancy notions is the so-called star discrepancy. Roughly speaking, a point set of low star discrepancy value allows for a small approximation error in quasi-Monte Carlo integration. It is thus the most studied discrepancy notion. In this work we present a new algorithm to compute point sets of low star discrepancy… CONTINUE READING
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