PYOMO Model Checking, Testing the optimisation model

[MUHAMMAD WAQAS SWATI]

I have a resource scheduling optimisation model in Pyomo with 3 constraints and an objective. The model runs well for the minimisation and maximisation objectives.

Constraint1: Each job is assigned to some machine.
Constraint2: Demand job <= Capacity of the machine.
Constraint3: Each job must be assigned to almost 1 machine.

Objective: MIN(Jobs placement cost on different machines)

Now, I want to write a  separate function that verifies my PYOMO model's result is "as" expected.

I mean the function will confirm that my model validates all the constraints before the results. Looking for some directions.

[David Woodruff]

You want something like this:

pyo.assert_optimal_termination(results)

Here's a little context:

import pyomo.environ as pyo

...

opt = pyo.SolverFactory('glpk')
results = opt.solve(model)  # solves and updates model
pyo.assert_optimal_termination(results)

If your library has this book, you might want to look at it:

Pyomo ― Optimization Modeling in Python (Springer Optimization and Its Applications, 67) 3rd ed. 2021 Edition

(The assert_optimal_termination function is in the third edition, but not the second edition)

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[MUHAMMAD WAQAS SWATI]

Thank You Sir for the guidance. I have studied the termination condition from the book. Actually, it terminates when the solver failed to return an optimal solution for the pyomo model...
However, I want a different function that works in the same way as my pyomo model and confirms that all constraints are met and the objective function's output is what was anticipated.