@@ -24,16 +24,16 @@ Using Persistent Solvers
2424The first step in using a persistent solver is to create a Pyomo model
2525as usual.
2626
27- >>> import pyomo.environ as pe
28- >>> m = pe .ConcreteModel()
29- >>> m.x = pe .Var()
30- >>> m.y = pe .Var()
31- >>> m.obj = pe .Objective(expr = m.x** 2 + m.y** 2 )
32- >>> m.c = pe .Constraint(expr = m.y >= - 2 * m.x + 5 )
27+ >>> import pyomo.environ as pyo
28+ >>> m = pyo .ConcreteModel()
29+ >>> m.x = pyo .Var()
30+ >>> m.y = pyo .Var()
31+ >>> m.obj = pyo .Objective(expr = m.x** 2 + m.y** 2 )
32+ >>> m.c = pyo .Constraint(expr = m.y >= - 2 * m.x + 5 )
3333
3434You can create an instance of a persistent solver through the SolverFactory.
3535
36- >>> opt = pe .SolverFactory(' gurobi_persistent' # doctest: +SKIP
36+ >>> opt = pyo .SolverFactory(' gurobi_persistent' # doctest: +SKIP
3737
3838This returns an instance of :py:class: `GurobiPersistent `. Now we need
3939to tell the solver about our model.
@@ -48,7 +48,7 @@ variables and constraints. We can now solve the model.
4848We can also add or remove variables, constraints, blocks, and
4949objectives. For example,
5050
51- >>> m.c2 = pe .Constraint(expr = m.y >= m.x) # doctest: +SKIP
51+ >>> m.c2 = pyo .Constraint(expr = m.y >= m.x) # doctest: +SKIP
5252>>> opt.add_constraint(m.c2) # doctest: +SKIP
5353
5454This tells the solver to add one new constraint but otherwise leave
@@ -69,29 +69,29 @@ code will run without error, but the solver will have an extra
6969constraint. The solver will have both y >= -2*x + 5 and y <= x, which
7070is not what was intended!
7171
72- >>> m = pe .ConcreteModel() # doctest: +SKIP
73- >>> m.x = pe .Var() # doctest: +SKIP
74- >>> m.y = pe .Var() # doctest: +SKIP
75- >>> m.c = pe .Constraint(expr = m.y >= - 2 * m.x + 5 ) # doctest: +SKIP
76- >>> opt = pe .SolverFactory(' gurobi_persistent' # doctest: +SKIP
72+ >>> m = pyo .ConcreteModel() # doctest: +SKIP
73+ >>> m.x = pyo .Var() # doctest: +SKIP
74+ >>> m.y = pyo .Var() # doctest: +SKIP
75+ >>> m.c = pyo .Constraint(expr = m.y >= - 2 * m.x + 5 ) # doctest: +SKIP
76+ >>> opt = pyo .SolverFactory(' gurobi_persistent' # doctest: +SKIP
7777>>> opt.set_instance(m) # doctest: +SKIP
7878>>> # WRONG:
7979>>> del m.c # doctest: +SKIP
80- >>> m.c = pe .Constraint(expr = m.y <= m.x) # doctest: +SKIP
80+ >>> m.c = pyo .Constraint(expr = m.y <= m.x) # doctest: +SKIP
8181>>> opt.add_constraint(m.c) # doctest: +SKIP
8282
8383The correct way to do this is:
8484
85- >>> m = pe .ConcreteModel() # doctest: +SKIP
86- >>> m.x = pe .Var() # doctest: +SKIP
87- >>> m.y = pe .Var() # doctest: +SKIP
88- >>> m.c = pe .Constraint(expr = m.y >= - 2 * m.x + 5 ) # doctest: +SKIP
89- >>> opt = pe .SolverFactory(' gurobi_persistent' # doctest: +SKIP
85+ >>> m = pyo .ConcreteModel() # doctest: +SKIP
86+ >>> m.x = pyo .Var() # doctest: +SKIP
87+ >>> m.y = pyo .Var() # doctest: +SKIP
88+ >>> m.c = pyo .Constraint(expr = m.y >= - 2 * m.x + 5 ) # doctest: +SKIP
89+ >>> opt = pyo .SolverFactory(' gurobi_persistent' # doctest: +SKIP
9090>>> opt.set_instance(m) # doctest: +SKIP
9191>>> # Correct:
9292>>> opt.remove_constraint(m.c) # doctest: +SKIP
9393>>> del m.c # doctest: +SKIP
94- >>> m.c = pe .Constraint(expr = m.y <= m.x) # doctest: +SKIP
94+ >>> m.c = pyo .Constraint(expr = m.y <= m.x) # doctest: +SKIP
9595>>> opt.add_constraint(m.c) # doctest: +SKIP
9696
9797.. warning :: Components removed from a pyomo model must be removed
@@ -100,14 +100,14 @@ The correct way to do this is:
100100Additionally, unexpected behavior may result if a component is
101101modified before being removed.
102102
103- >>> m = pe .ConcreteModel() # doctest: +SKIP
104- >>> m.b = pe .Block() # doctest: +SKIP
105- >>> m.b.x = pe .Var() # doctest: +SKIP
106- >>> m.b.y = pe .Var() # doctest: +SKIP
107- >>> m.b.c = pe .Constraint(expr = m.b.y >= - 2 * m.b.x + 5 ) # doctest: +SKIP
108- >>> opt = pe .SolverFactory(' gurobi_persistent' # doctest: +SKIP
103+ >>> m = pyo .ConcreteModel() # doctest: +SKIP
104+ >>> m.b = pyo .Block() # doctest: +SKIP
105+ >>> m.b.x = pyo .Var() # doctest: +SKIP
106+ >>> m.b.y = pyo .Var() # doctest: +SKIP
107+ >>> m.b.c = pyo .Constraint(expr = m.b.y >= - 2 * m.b.x + 5 ) # doctest: +SKIP
108+ >>> opt = pyo .SolverFactory(' gurobi_persistent' # doctest: +SKIP
109109>>> opt.set_instance(m) # doctest: +SKIP
110- >>> m.b.c2 = pe .Constraint(expr = m.b.y <= m.b.x) # doctest: +SKIP
110+ >>> m.b.c2 = pyo .Constraint(expr = m.b.y <= m.b.x) # doctest: +SKIP
111111>>> # ERROR: The constraint referenced by m.b.c2 does not
112112>>> # exist in the solver model.
113113>>> opt.remove_block(m.b) # doctest: +SKIP
@@ -117,12 +117,12 @@ the solver instance, modify it with Pyomo, and then add it back to the
117117solver instance. The only exception is with variables. Variables may
118118be modified and then updated with with solver:
119119
120- >>> m = pe .ConcreteModel() # doctest: +SKIP
121- >>> m.x = pe .Var() # doctest: +SKIP
122- >>> m.y = pe .Var() # doctest: +SKIP
123- >>> m.obj = pe .Objective(expr = m.x** 2 + m.y** 2 ) # doctest: +SKIP
124- >>> m.c = pe .Constraint(expr = m.y >= - 2 * m.x + 5 ) # doctest: +SKIP
125- >>> opt = pe .SolverFactory(' gurobi_persistent' # doctest: +SKIP
120+ >>> m = pyo .ConcreteModel() # doctest: +SKIP
121+ >>> m.x = pyo .Var() # doctest: +SKIP
122+ >>> m.y = pyo .Var() # doctest: +SKIP
123+ >>> m.obj = pyo .Objective(expr = m.x** 2 + m.y** 2 ) # doctest: +SKIP
124+ >>> m.c = pyo .Constraint(expr = m.y >= - 2 * m.x + 5 ) # doctest: +SKIP
125+ >>> opt = pyo .SolverFactory(' gurobi_persistent' # doctest: +SKIP
126126>>> opt.set_instance(m) # doctest: +SKIP
127127>>> m.x.setlb(1.0 ) # doctest: +SKIP
128128>>> opt.update_var(m.x) # doctest: +SKIP
@@ -160,13 +160,13 @@ Persistent Solver Performance
160160In order to get the best performance out of the persistent solvers, use the
161161"save_results" flag:
162162
163- >>> import pyomo.environ as pe
164- >>> m = pe .ConcreteModel()
165- >>> m.x = pe .Var()
166- >>> m.y = pe .Var()
167- >>> m.obj = pe .Objective(expr = m.x** 2 + m.y** 2 )
168- >>> m.c = pe .Constraint(expr = m.y >= - 2 * m.x + 5 )
169- >>> opt = pe .SolverFactory(' gurobi_persistent' # doctest: +SKIP
163+ >>> import pyomo.environ as pyo
164+ >>> m = pyo .ConcreteModel()
165+ >>> m.x = pyo .Var()
166+ >>> m.y = pyo .Var()
167+ >>> m.obj = pyo .Objective(expr = m.x** 2 + m.y** 2 )
168+ >>> m.c = pyo .Constraint(expr = m.y >= - 2 * m.x + 5 )
169+ >>> opt = pyo .SolverFactory(' gurobi_persistent' # doctest: +SKIP
170170>>> opt.set_instance(m) # doctest: +SKIP
171171>>> results = opt.solve(save_results = False ) # doctest: +SKIP
172172
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