Ramaswamy, V. P., & Szeider, S. (2023). Proven Optimally-Balanced Latin Rectangles with SAT. In R. Yap (Ed.), 29th International Conference on Principles and Practice of Constraint Programming (CP 2023). Schloss-Dagstuhl - Leibniz Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CP.2023.48
29th International Conference on Principles and Practice of Constraint Programming (CP 2023)
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Event date:
27-Aug-2023 - 31-Aug-2023
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Event place:
Toronto, Canada
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Number of Pages:
10
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Publisher:
Schloss-Dagstuhl - Leibniz Zentrum für Informatik
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Peer reviewed:
Yes
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Keywords:
arithmetic constraints; certified optimality; combinatorial design; SAT encodings; spatially balanced Latin rectangles
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Abstract:
Motivated by applications from agronomic field experiments, Díaz, Le Bras, and Gomes [CPAIOR 2015] introduced Partially Balanced Latin Rectangles as a generalization of Spatially Balanced Latin Squares. They observed that the generation of Latin rectangles that are optimally balanced is a highly challenging computational problem. They computed, utilizing CSP and MIP encodings, Latin rectangles up to 12 × 12, some optimally balanced, some suboptimally balanced. In this paper, we develop a SAT encoding for generating balanced Latin rectangles. We compare experimentally encoding variants. Our results indicate that SAT encodings perform competitively with the MIP encoding, in some cases better. In some cases we could find Latin rectangles that are more balanced than previously known ones. This finding is significant, as there are many arithmetic constraints involved. The SAT approach offers the advantage that we can certify that Latin rectangles are optimally balanced through DRAT proofs that can be verified independently.
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Project title:
Strukturerkennung mit SAT: P36420-N (FWF - Österr. Wissenschaftsfonds) Revealing and Utilizing the Hidden Structure for Solving Hard Problems in AI: ICT19-065 (WWTF Wiener Wissenschafts-, Forschu und Technologiefonds)