Use MiniZinc

Use MiniZinc for decision problems that naturally fit a constraint programming (CP) model. It works well for discrete constraint satisfaction problems and models that benefit from CP global constraints.

Capabilities

• Supports constraint programming (CP) and discrete optimization.

Limitations

• Does not support continuous decision variables.
• Only the Chuffed backend is currently exposed.
• MiniZinc requires a single, scalar objective.

Example

Create a Problem with Integer model type and pass "minizinc" to .solve() to use the MiniZinc backend:

from relationalai.semantics import Integer, Model
from relationalai.semantics.reasoners.prescriptive import Problem

m = Model("DiscreteExample")

# ... model definition ...

p = Problem(m, Integer)

# ... problem definition ...

p.solve("minizinc")

Related resources:

• Solve a decision problem
• Browse prescriptive reasoning templates

Note that:

• MiniZinc requires Problem(m, Integer). If you use Float, you will typically get type or compilation errors.
• MiniZinc runs through a MiniZinc backend. In current deployments, PyRel uses the Chuffed backend.

Version and licensing

MiniZinc is bundled and does not require a license key or additional Snowflake setup.

Detail	Info
Version	2.8.5
License	MPL 2.0 (free and open source)

Resources

• MiniZinc documentation

Where to go next

Solve a decision problemLearn the prescriptive workflow for declaring decision variables, adding requirements and an objective, solving, and reading results.

Browse prescriptive reasoning templatesExplore prescriptive templates you can adapt to your own problems.