Exploiting Monotonicity in Interval Constraint Propagation

Ignacio Araya, Gilles Trombettoni, Bertrand Neveu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

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.

Original languageEnglish
Title of host publicationProceedings of the 24th AAAI Conference on Artificial Intelligence, AAAI 2010
PublisherAAAI Press
Pages9-14
Number of pages6
ISBN (Electronic)9781577354642
StatePublished - 15 Jul 2010
Externally publishedYes
Event24th AAAI Conference on Artificial Intelligence, AAAI 2010 - Atlanta, United States
Duration: 11 Jul 201015 Jul 2010

Publication series

NameProceedings of the 24th AAAI Conference on Artificial Intelligence, AAAI 2010

Conference

Conference24th AAAI Conference on Artificial Intelligence, AAAI 2010
Country/TerritoryUnited States
CityAtlanta
Period11/07/1015/07/10

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