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An adapter for the Python-MIP from/to OMMX.

Project description

OMMX adapter for Python-MIP

PyPI - Version

This package provides an adapter for the Python-MIP from/to OMMX

Python-MIP as a solver in OMMX toolchain

sequenceDiagram
    participant U as User
    participant A as Adapter
    participant P as Python-MIP
    U->>A: ommx.v1.Instance
    A->>U: Python-MIP model
    U->>P: Python-MIP model and Parameters for Python-MIP;
    P->>P: Solve with CBC, Gurobi, or other solvers
    P->>U: Optimized model
    U->>A: Optimized model and ommx.v1.Instance
    A->>U: ommx.v1.Solution

Python-MIP as a user interface to create OMMX instance

sequenceDiagram
    participant U as User
    participant A as Adapter
    participant O as Other OMMX toolchain
    U->>A: Python-MIP model
    A->>U: ommx.v1.Instance
    U->>O: ommx.v1.Instance and Parameters for other solver
    O->>O: Solve the instance with other solver using other adapter
    O->>U: ommx.v1.Solution

Usage

ommx-python-mip-adapter can be installed from PyPI as follows:

pip install ommx-python-mip-adapter

Python-MIP can be used through ommx-python-mip-adapter by using the following:

import ommx_python_mip_adapter as adapter
from ommx.v1 import Instance, DecisionVariable

x1 = DecisionVariable.integer(1, lower=0, upper=5)
ommx_instance = Instance.from_components(
    decision_variables=[x1],
    objective=x1,
    constraints=[],
    sense=Instance.MINIMIZE,
)

# Convert from `ommx.v1.Instance` to `mip.Model`
model = adapter.instance_to_model(ommx_instance)
model.optimize()
# Create `ommx.v1.State` from Optimized `mip.Model`
ommx_state = adapter.model_to_state(model, ommx_instance)

print(ommx_state)

You can get ommx.v1.Instance from a Python-MIP model as the following:

import mip
import ommx_python_mip_adapter as adapter

model = mip.Model()
x1=model.add_var(name="1", var_type=mip.INTEGER, lb=0, ub=5)
x2=model.add_var(name="2", var_type=mip.CONTINUOUS, lb=0, ub=5)
model.objective = - x1 - 2 * x2
model.add_constr(x1 + x2 - 6 <= 0)

ommx_instance = adapter.model_to_instance(model)

print(ommx_instance)

Reference

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