The SeqBin Constraint Revisited

TL;DR

This paper revisits the SeqBin constraint, identifies flaws in existing algorithms, and proposes a new, more efficient propagator that ensures domain consistency and improves performance for important global constraints.

Contribution

It introduces a new propagator for SeqBin that overcomes previous limitations, ensuring domain consistency and better efficiency, especially for related global constraints.

Findings

New propagator enforces domain consistency in O(nd^2) time.

Special cases of SeqBin are handled in O(nd) time.

The improved algorithm overcomes bounds disentailment and idempotency issues.

Abstract

We revisit the SeqBin constraint. This meta-constraint subsumes a number of important global constraints like Change, Smooth and IncreasingNValue. We show that the previously proposed filtering algorithm for SeqBin has two drawbacks even under strong restrictions: it does not detect bounds disentailment and it is not idempotent. We identify the cause for these problems, and propose a new propagator that overcomes both issues. Our algorithm is based on a connection to the problem of finding a path of a given cost in a restricted $n$-partite graph. Our propagator enforces domain consistency in O(nd^2) and, for special cases of SeqBin that include Change, Smooth and IncreasingNValue, in O(nd) time.