### Abstract

We describe a randomized algorithm that, given a set of points in the plane, computes the best location to insert a new point, such that the Delaunay triangulation of the resulting point set has the largest possible minimum angle. The expected running time of our algorithm is at most cubic on any input, improving the roughly quartic time of the best previously known algorithm.

Original language | English (US) |
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Title of host publication | CCCG 2013 - 25th Canadian Conference on Computational Geometry |

Publisher | Canadian Conference on Computational Geometry |

Pages | 259-263 |

Number of pages | 5 |

State | Published - 2013 |

Event | 25th Canadian Conference on Computational Geometry, CCCG 2013 - Waterloo, Canada Duration: Aug 8 2013 → Aug 10 2013 |

### Other

Other | 25th Canadian Conference on Computational Geometry, CCCG 2013 |
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Country | Canada |

City | Waterloo |

Period | 8/8/13 → 8/10/13 |

### Fingerprint

### ASJC Scopus subject areas

- Geometry and Topology
- Computational Mathematics

### Cite this

*CCCG 2013 - 25th Canadian Conference on Computational Geometry*(pp. 259-263). Canadian Conference on Computational Geometry.

**How to place a point to maximize angles.** / Aronov, Boris; Yagnatinsky, Mark V.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*CCCG 2013 - 25th Canadian Conference on Computational Geometry.*Canadian Conference on Computational Geometry, pp. 259-263, 25th Canadian Conference on Computational Geometry, CCCG 2013, Waterloo, Canada, 8/8/13.

}

TY - GEN

T1 - How to place a point to maximize angles

AU - Aronov, Boris

AU - Yagnatinsky, Mark V.

PY - 2013

Y1 - 2013

N2 - We describe a randomized algorithm that, given a set of points in the plane, computes the best location to insert a new point, such that the Delaunay triangulation of the resulting point set has the largest possible minimum angle. The expected running time of our algorithm is at most cubic on any input, improving the roughly quartic time of the best previously known algorithm.

AB - We describe a randomized algorithm that, given a set of points in the plane, computes the best location to insert a new point, such that the Delaunay triangulation of the resulting point set has the largest possible minimum angle. The expected running time of our algorithm is at most cubic on any input, improving the roughly quartic time of the best previously known algorithm.

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UR - http://www.scopus.com/inward/citedby.url?scp=84961387003&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84961387003

SP - 259

EP - 263

BT - CCCG 2013 - 25th Canadian Conference on Computational Geometry

PB - Canadian Conference on Computational Geometry

ER -