MiniZinc is an open-source constraint modeling language and solver. It allows users to model constraint satisfaction and optimization problems in a high-level, solver-independent format. Models are then compiled into FlatZinc code and solved by a backend solver.
MiniZinc: High-Level Constraint Modeling Language and Solver
MiniZinc is an open-source constraint modeling language and solver. It allows users to model constraint satisfaction and optimization problems in a high-level, solver-independent format. Models are then compiled into FlatZinc code and solved by a backend solver.
What is MiniZinc?
MiniZinc is an open-source constraint modeling language and solver developed at Monash University, NICTA, and Data61 in Australia. It provides a high-level, solver-independent language for modeling constraint satisfaction and optimization problems. Some key features of MiniZinc include:
Expressive modeling language allowing the natural expression of complex, real-world constraints
Support for integers, floats, Booleans, sets, arrays and more
High-level global constraints like all-different, cumulative, and element
Control flow statements like if-then-else, for loops, let expressions
Solver-independent modeling - compilation to FlatZinc targets allows connecting to many solvers
Open-source with an active developer and user community
MiniZinc models are compiled into the lower-level FlatZinc format which can then be solved by constraint solvers like Gecode, Chuffed, CBC, Gurobi and more. This allows users to focus on declarative, high-level modeling without worrying about solver-specific code. MiniZinc comes with an IDE and debugging tools for creating and testing models. Its expressiveness, solver integration and active community has made it popular for teaching and research in constraint programming.
MiniZinc Features
Features
High-level modeling language
Solver-independent
Open-source
Supports constraint satisfaction and optimization problems
Large library of global constraints
Interfaces with many solvers like Gecode, Chuffed, CPLEX, Gurobi etc.
Pricing
Open Source
Pros
Declarative language allows focus on modeling
Many solvers supported
Active development community
Used for education and in industry
Cons
Limited debugging capabilities
No native support for nonlinear constraints
Not as fast as solver-specific APIs for some problems
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