Boosting Combinatorial Search Through Randomization

Abstract

Unpredictability in the running time of complete search procedures can often be explained by the phenomenon of "heavy-tailed cost distributions", meaning that at any time during the experiment there is a non-negligible probability of hitting a problem that requires exponentially more time to solve than any that has been encountered before (Gomes et al. 1998a). We present a general method for introducing controlled randomization into complete search algorithms. The "boosted" search methods provably eliminate heavy-tails to the right of the median. Furthermore, they can take advantage of heavy-tails to the left of the median (that is, a nonnegligible chance of very short runs) to dramatically shorten the solution time. We demonstrate speedups of several orders of magnitude for state-of-the-art complete search procedures running on hard, real-world problems. Introduction The time required by complete search methods to solve similar combinatorial problems can be surprisingl...

Cite

Text

Gomes et al. "Boosting Combinatorial Search Through Randomization." AAAI Conference on Artificial Intelligence, 1998.

Markdown

[Gomes et al. "Boosting Combinatorial Search Through Randomization." AAAI Conference on Artificial Intelligence, 1998.](https://mlanthology.org/aaai/1998/gomes1998aaai-boosting/)

BibTeX

@inproceedings{gomes1998aaai-boosting,
  title     = {{Boosting Combinatorial Search Through Randomization}},
  author    = {Gomes, Carla P. and Selman, Bart and Kautz, Henry A.},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {1998},
  pages     = {431-437},
  url       = {https://mlanthology.org/aaai/1998/gomes1998aaai-boosting/}
}