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.V24I1.7541Markdown
[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.V24I1.7541BibTeX
@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/}
}