1 research outputs found
A Comparison of Lex Bounds for Multiset Variables in Constraint Programming
Set and multiset variables in constraint programming have typically been
represented using subset bounds. However, this is a weak representation that
neglects potentially useful information about a set such as its cardinality.
For set variables, the length-lex (LL) representation successfully provides
information about the length (cardinality) and position in the lexicographic
ordering. For multiset variables, where elements can be repeated, we consider
richer representations that take into account additional information. We study
eight different representations in which we maintain bounds according to one of
the eight different orderings: length-(co)lex (LL/LC), variety-(co)lex (VL/VC),
length-variety-(co)lex (LVL/LVC), and variety-length-(co)lex (VLL/VLC)
orderings. These representations integrate together information about the
cardinality, variety (number of distinct elements in the multiset), and
position in some total ordering. Theoretical and empirical comparisons of
expressiveness and compactness of the eight representations suggest that
length-variety-(co)lex (LVL/LVC) and variety-length-(co)lex (VLL/VLC) usually
give tighter bounds after constraint propagation. We implement the eight
representations and evaluate them against the subset bounds representation with
cardinality and variety reasoning. Results demonstrate that they offer
significantly better pruning and runtime.Comment: 7 pages, Proceedings of the Twenty-Fifth AAAI Conference on
Artificial Intelligence (AAAI-11