Pyomo: Access Solution From Python Code

Question

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,

Answer 1

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)