MiniZinc

MiniZinc is a free and open-source constraint modelling language. It allows users to describe constraint satisfaction and optimization problems in a high-level, solver-independent way. The MiniZinc language focuses on what the problem is, rather than how to solve it, abstracting away the implementation details specific to particular solvers.

The core principle behind MiniZinc is to separate the model of a problem from the solver used to find a solution. This separation enables users to experiment with different solvers, compare their performance, and easily adapt the model to different problem instances without altering the fundamental problem definition.

MiniZinc models are typically compiled into FlatZinc, an intermediate, solver-specific representation. This compilation is performed by the MiniZinc compiler. FlatZinc acts as a common language understood by a variety of constraint solvers, allowing them to process the same model.

Key features of MiniZinc include:

• Declarative Modelling: Problems are described using mathematical notation and constraints, focusing on the logical relationships between variables.
• Solver Independence: Models can be solved with various constraint programming solvers (e.g., Gecode, Chuffed, OR-Tools) and mathematical programming solvers (e.g., Gurobi, CPLEX).
• Data Separation: Problem data can be separated from the model, facilitating experimentation with different problem instances.
• Global Constraints: MiniZinc provides a rich set of built-in global constraints that capture common patterns in constraint problems. These constraints are often implemented efficiently by solvers.
• Arrays and Sets: MiniZinc supports arrays and sets, providing a flexible way to represent structured data within the model.
• Extensibility: MiniZinc can be extended with user-defined functions and constraints.

MiniZinc is used in a wide range of applications, including scheduling, resource allocation, vehicle routing, and combinatorial optimization. It provides a powerful and flexible tool for modelling and solving complex problems.