Exploiting Monotonicity in Interval Constraint Propagation

Abstract

We propose in this paper a new interval constraint propagation algorithm, called MOnotonic Hull Consistency (Mohc), that exploits monotonicity of functions. The propagation is standard, but the Mohc-Revise procedure, used to filter/contract the variable domains w.r.t. an individual constraint, uses monotonic versions of the classical HC4-Revise and BoxNarrow procedures. Mohc-Revise appears to be the first adaptive revise procedure ever proposed in (interval) constraint programming.  Also, when a function is monotonic w.r.t. every variable, Mohc-Revise is proven to compute the optimal/sharpest box enclosing all the solutions of the corresponding constraint (hull consistency). Very promising experimental results suggest that Mohc has the potential to become an alternative to the state-of-the-art HC4 and Box algorithms.

Cite

Text

Araya et al. "Exploiting Monotonicity in Interval Constraint Propagation." AAAI Conference on Artificial Intelligence, 2010. doi:10.1609/AAAI.V24I1.7541

Markdown

[Araya et al. "Exploiting Monotonicity in Interval Constraint Propagation." AAAI Conference on Artificial Intelligence, 2010.](https://mlanthology.org/aaai/2010/araya2010aaai-exploiting/) doi:10.1609/AAAI.V24I1.7541

BibTeX

@inproceedings{araya2010aaai-exploiting,
  title     = {{Exploiting Monotonicity in Interval Constraint Propagation}},
  author    = {Araya, Ignacio and Trombettoni, Gilles and Neveu, Bertrand},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2010},
  pages     = {9-14},
  doi       = {10.1609/AAAI.V24I1.7541},
  url       = {https://mlanthology.org/aaai/2010/araya2010aaai-exploiting/}
}