,
Cèsar Fernández Camón
,
Carles Mateu Piñol
Creative Commons Attribution 4.0 International license
Despite the utility of Maximum Satisfiability (MaxSAT) in discrete optimization, developing iterative workflows remains cumbersome due to fragmented, low-level solver APIs. We present Hermax, a unified Python library and modelling compiler for MaxSAT. Hermax provides an IPAMIR interface that exposes incremental solving, assumptions, and weight updates through a single API across many incremental and non-incremental backends. Furthermore, it introduces a compiler with Constraint Programming primitives that translates high-level models directly into optimized CNF/WCNF through eager evaluation. This compiler allows automatic optimizations like integer ladder graph encoding that bypasses Pseudo-Boolean formulation when possible. Together, these features enable rapid prototyping and production grade optimization directly from Python across major platforms and hardware architectures.
@InProceedings{salviahornos_et_al:LIPIcs.SAT.2026.41,
author = {Salvia Hornos, Josep Maria and Fern\'{a}ndez Cam\'{o}n, C\`{e}sar and Mateu Pi\~{n}ol, Carles},
title = {{Hermax: A Unified MaxSAT Library}},
booktitle = {29th International Conference on Theory and Applications of Satisfiability Testing (SAT 2026)},
pages = {41:1--41:13},
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.2026.41},
URN = {urn:nbn:de:0030-drops-263478},
doi = {10.4230/LIPIcs.SAT.2026.41},
annote = {Keywords: MaxSAT, Incremental Solving, IPAMIR, Python, Constraint modelling}
}