I have a linear integer programme I want to solve. I installed solver glpk (thanks to this answer) and pyomo. I wrote code like this:
from pyomo.environ import *
from pyomo.opt import SolverFactory
a = 370
b = 420
c = 2
model = ConcreteModel()
model.x = Var([1,2], domain=NonNegativeIntegers)
model.Objective = Objective(expr = a * model.x[1] + b * model.x[2], sense=minimize)
model.Constraint1 = Constraint(expr = model.x[1] + model.x[2] == c)
# ... more constraints
opt = SolverFactory('glpk')
results = opt.solve(model)
This produces solution to file results.yaml
.
I have many problems I want to solve using the same model but with different a
, b
, and c
values. I want to assign different values to a
, b
, and c
, solve the model, obtain solution of model.x[1]
and model.x[2]
, and have a listing of a
, b
, c
, model.x[1]
and model.x[2]
. I read documentation but examples only write solutions to file such as results.yaml
.
Is there any way I can access to solution values from code?
Thanks,
Here's a modified version of your script that illustrates two different ways of printing variable values: (1) by explicitly referencing each variable and (2) by iterating over all variables in the model.
# Pyomo v4.4.1
# Python 2.7
from pyomo.environ import *
from pyomo.opt import SolverFactory
a = 370
b = 420
c = 4
model = ConcreteModel()
model.x = Var([1,2], domain=Binary)
model.y = Var([1,2], domain=Binary)
model.Objective = Objective(expr = a * model.x[1] + b * model.x[2] + (a-b)*model.y[1] + (a+b)*model.y[2], sense=maximize)
model.Constraint1 = Constraint(expr = model.x[1] + model.x[2] + model.y[1] + model.y[2] <= c)
opt = SolverFactory('glpk')
results = opt.solve(model)
#
# Print values for each variable explicitly
#
print("Print values for each variable explicitly")
for i in model.x:
print str(model.x[i]), model.x[i].value
for i in model.y:
print str(model.y[i]), model.y[i].value
print("")
#
# Print values for all variables
#
print("Print values for all variables")
for v in model.component_data_objects(Var):
print str(v), v.value
Here's the output generated:
Print values for each variable explicitly
x[1] 1.0
x[2] 1.0
y[1] 0.0
y[2] 1.0
Print values for all variables
x[1] 1.0
x[2] 1.0
y[1] 0.0
y[2] 1.0
I'm not sure if this is what you are looking for, but this is a way that I have some variables being printed in one of my scripts.
from pyomo.environ import *
from pyomo.opt import SolverFactory
from pyomo.core import Var
M = AbstractModel()
opt = SolverFactory('glpk')
# Vars, Params, Objective, Constraints....
instance = M.create_instance('input.dat') # reading in a datafile
results = opt.solve(instance, tee=True)
results.write()
instance.solutions.load_from(results)
for v in instance.component_objects(Var, active=True):
print ("Variable",v)
varobject = getattr(instance, str(v))
for index in varobject:
print (" ",index, varobject[index].value)
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