CPMpy: Translating High-Level Constraint Models to Multiple Solver Paradigms

A new arXiv paper (2608.15143) introduces CPMpy, a framework for translating high-level constraint satisfaction and optimization problems into multiple lower-level formalisms, including CP, SMT QF-LIA, ILP, PB, and (Max)SAT. The work addresses the challenge of comparing different constraint-solving technologies for a given problem without requiring manual remodeling for each paradigm. The authors define a high-level language of logical and arithmetic operations, along with additional functions and constraints, to facilitate automatic translation. This approach enables users to specify problems declaratively and then automatically generate models for various solvers, potentially improving performance by selecting the best-suited technology. The paper is available on arXiv and represents a contribution to the field of constraint programming and automated reasoning.