Akgün, Özgür, Gent, Ian Philip, Jefferson, Christopher et al. (5 more authors) (2025) TabID: Automatic Identification and Tabulation of Subproblems in Constraint Models. Journal of Artificial Intelligence Research (JAIR). pp. 1999-2056. ISSN 1076-9757
Abstract
The performance of a constraint model can often be improved by converting a subproblem into a single table constraint (referred to as tabulation). Finding subproblems to tabulate is traditionally a manual and time-intensive process, even for expert modellers. This paper presents TabID, an entirely automated method to identify promising subproblems for tabulation in constraint programming. We introduce a diverse set of heuristics designed to identify promising candidates for tabulation, aiming to improve solver performance. These heuristics are intended to encapsulate various factors that contribute to useful tabulation. We also present additional checks to limit the potential drawbacks of suboptimal tabulation. We comprehensively evaluate our approach using benchmark problems from existing literature that previously relied on manual identification by constraint programming experts of constraints to tabulate. We demonstrate that our automated identification and tabulation process achieves comparable, and in some cases improved results. We empirically evaluate the efficacy of our approach on a variety of solvers, including standard CP (Minion and Gecode), clause-learning CP (Chuffed and OR-Tools) and SAT solvers (Kissat). Our findings highlight the substantial potential of fully automated tabulation, suggesting its integration into automated model reformulation tools.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | ©2025 The Authors. Published by AI Access Foundation. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Funding Information: | Funder Grant number EPSRC EP/W001977/1 |
Depositing User: | Pure (York) |
Date Deposited: | 07 Apr 2025 10:40 |
Last Modified: | 07 Apr 2025 10:40 |
Published Version: | https://doi.org/10.1613/jair.1.17032 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1613/jair.1.17032 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:225249 |