,
Ignace Bleukx
,
Tias Guns
Creative Commons Attribution 4.0 International license
Many communities within Combinatorial Optimization (CO) maintain benchmark sets in heterogeneous formats, often tied to specific competitions and solver technologies. Whilst this diversity is of practical and historical importance, it also creates barriers to use and compare methods from different communities. Inspired by the more unified software ecosystem from the ML community, we propose a programmatic abstraction for CO benchmark sets. A unified programmatic interface for downloading, reading and converting datasets across formats. This includes solver-oriented benchmarks such as XCSP3, MIPLib, PB, MaxSATEval, SAT and application-oriented benchmarks such as Nurse rostering, PSPLib (RCSP), and JSPlib. To enable cross-formalism conversions, we provide loaders that bring these dataset instances into CPMpy, a modelling library for constraint programming. CPMpy provides a transformation stack; an extensive set of rewrite operations such as constraint decomposition, linearization, and Boolean encodings, that allow transforming between different constraint formalisms. Based on this, we implement file writers to multiple solver-oriented formats, including MiniZinc, LP file format (ILP), OPB, and DIMACS (W)CNF ((Max)SAT). We demonstrate that this unified abstraction facilitates cross-community access to benchmarks and systematic comparisons of solvers across paradigms.
@InProceedings{sergeys_et_al:LIPIcs.SAT.2026.42,
author = {Sergeys, Thomas and Bleukx, Ignace and Guns, Tias},
title = {{Unified Programmatic Access to CO Benchmarks, to Connect Constraint Solving Communities}},
booktitle = {29th International Conference on Theory and Applications of Satisfiability Testing (SAT 2026)},
pages = {42:1--42:11},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-431-4},
ISSN = {1868-8969},
year = {2026},
volume = {377},
editor = {Ignatiev, Alexey and Szeider, Stefan},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SAT.2026.42},
URN = {urn:nbn:de:0030-drops-263485},
doi = {10.4230/LIPIcs.SAT.2026.42},
annote = {Keywords: CPMpy, datasets, benchmarking, constraint solving}
}
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