Encoding Multi-Valued Decision Diagram Constraints as Binary Constraint Trees

Authors

  • Ruiwei Wang National University of Singapore, Singapore
  • Roland H.C. Yap National University of Singapore, Singapore

DOI:

https://doi.org/10.1609/aaai.v36i4.20300

Keywords:

Constraint Satisfaction And Optimization (CSO)

Abstract

Ordered Multi-valued Decision Diagram (MDD) is a compact representation used to model various constraints, such as regular constraints and table constraints. It can be particularly useful for representing ad-hoc problem specific constraints. Many algorithms have been proposed to enforce Generalized Arc Consistency (GAC) on MDD constraints. In this paper, we introduce a new compact representation called Binary Constraint Tree (BCT). We propose tree binary encodings to transform any MDD constraint into a BCT constraint. We also present a specialized algorithm enforcing GAC on the BCT constraint resulting from a MDD constraint. Experimental results on a large set of benchmarks show that the BCT GAC algorithm can significantly outperform state-of-the-art MDD as well as table GAC algorithms.

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Published

2022-06-28

How to Cite

Wang, R., & Yap, R. H. (2022). Encoding Multi-Valued Decision Diagram Constraints as Binary Constraint Trees. Proceedings of the AAAI Conference on Artificial Intelligence, 36(4), 3850-3858. https://doi.org/10.1609/aaai.v36i4.20300

Issue

Section

AAAI Technical Track on Constraint Satisfaction and Optimization