MiniZinc2.10.1

Write a high-level model of a scheduling, allocation, or other constraint problem, then use MiniZinc to examine feasible solutions or optimize an objective without rewriting the model for each solver. MiniZinc provides a bundled language toolchain and IDE for expressing constraint satisfaction and optimization problems in a readable modeling language. Predefined constraint libraries let users describe rules and relationships at a high level, while the model remains separate from the engine that solves it. This separation allows one modeling approach to work with a range of supported solvers rather than locking the problem to a particular solver.

FlatZinc connects the human-oriented model with solver-specific processing for investigating candidate solutions and optimization results. Typical users include learners and educators studying formal problem solving, as well as others who need to represent and test structured constraints in an educational setting.

MiniZinc 2.10.1 runs on Linux with snapd and targets x86_64 (amd64) systems. It is open-source software developed by MiniZinc at Monash University in collaboration with Data61 Decision Sciences and the University of Melbourne. Listed in Education, it suits classroom exercises, solver experiments, and optimization models where changing the underlying solver should not require changing the problem description.