See the PyGurobi Github page for a tutorial pygurobi. A constraint set is composed of all constraints sharing the same string identifier before the indices: A 2,3,4 and A 1,2,3 are in the same constraint set, A; A 2,3,4 and B 2,3,4 are in constraint sets A and B, respectively PyGurobi by default assumes that constraint set names are separated from indices by round brackets " " and " ". For example, constraints look like env r,t - where "env" in the constraint set name and "r" and "t" are the index values. See the source for more details.
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Specify a callback for gurobi to use. Parameters: func function — The function to call. The function should have three arguments. The first will be the pyomo model being solved. The second will be the GurobiPersistent instance. The third will be an enum member of gurobipy. This will indicate where in the branch and bound algorithm gurobi is at. Parameters: param str — The gurobi parameter to set. Options include any gurobi parameter.
Please see the Gurobi documentation for options. See Gurobi documentation for possible values. This discards any existing model and starts from scratch. Parameters: model ConcreteModel — The pyomo model to be used with the solver.
Be careful with this. If a trivial constraint is skipped then that constraint cannot be removed from a persistent solver an error will be raised if a user tries to remove a non-existent constraint. This is useful for catching bugs. Ordinarily a fixed variable should appear as a constant value in the solver constraints.
If True, then the error will not be raised. Parameters: con pyomo. Note that, at least for now, any existing objective will be discarded. Other than that, any existing model components will remain intact. See the solver documentation for possible solver options.
IBM ILOG CPLEX Optimization Studio V12.9.0 documentation