solverfriendly

Solverfriendly is a term used in optimization, automated reasoning, and computer science to describe problem formulations, datasets, and software interfaces designed to be easily handled by solving engines such as MILP solvers, SAT/SMT solvers, and constraint programming systems. A solverfriendly formulation typically emphasizes clarity, compactness, and compatibility with standard solver input formats, with the goal of enabling fast, reliable solving across solvers and platforms.

Common characteristics include using canonical encodings (for example, linear or pseudo-Boolean representations for MILP and SAT respectively), minimizing the number of auxiliary variables, avoiding highly nonlinear or solver-specific constructs, and providing well-defined variable domains and objective functions. Interfaces may expose solver-neutral representations and offer straightforward translation to target solvers, facilitating benchmarking and portability. Good solverfriendly data and models are reproducible, well-documented, and free of solver-specific optimizations that obscure correctness.

Applications and domains include operations research modeling, puzzle and game solving, automated planning, verification, and benchmarking suites. In practice, solverfriendly practices help improve solving times, reduce debugging effort, and enable cross-solver comparisons.

Limitations include potential encoding overhead or loss of expressiveness when forcing solver-friendly forms, and the risk of overfitting models to a particular solver's strengths. The term is often encountered in academic and professional discussions of modeling guidelines and solver performance.