Date of Original Version

5-2012

Type

Conference Proceeding

Abstract or Description

We study stochastic variants of flow-based global constraints as combinatorial chance constraints. As a specific case study, we focus on the stochastic weighted alldifferent constraint. We first show that determining the consistency of this constraint is NP-hard. We then show how the combinatorial structure of the all different constraint can be used to define chance-based filtering, and to compute a policy. Our propagation algorithm can be extended immediately to related flow-based constraints such as the weighted cardinality constraint. The main benefits of our approach are that our chance-constrained global constraints can be integrated naturally in classical deterministic CP systems, and are more scalable than existing approaches for stochastic constraint programming.

DOI

10.1007/978-3-642-29828-8_9

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Published In

N. Beldiceanu, N. Jussien, and ´E. Pinson (Eds.): CPAIOR 2012, LNCS 7298, 129-145.