from warehouse_data import *
import pyomo.environ as pe
import warehouse_function as wf
# call function to create model
model = wf.create_wl_model(N, M, d, P)
# solve the model
solver = pe.SolverFactory('glpk')
solver_opt = dict()
solver_opt['log'] = 'warehouse.log'
solver_opt['nointopt'] = None
solver.solve(model, options=solver_opt)
# look at the solution
model.y.pprint()
import warnings
warnings.filterwarnings("ignore")
# @all:
from warehouse_data import *
from pyomo.environ import *
from pyomo.opt import TerminationCondition
import warehouse_function as wf
import matplotlib.pyplot as plt
# call function to create model
model = wf.create_wl_model(N, M, d, P)
model.integer_cuts = ConstraintList()
objective_values = list()
done = False
while not done:
# solve the model
solver = SolverFactory("glpk")
results = solver.solve(model)
objective_values.append(value(model.obj))
term_cond = results.solver.termination_condition
print("")
print("--- Solver Status: {0} ---".format(term_cond))
if term_cond != TerminationCondition.optimal:
done = True
else:
# look at the solution
print("Optimal Obj. Value = {0}".format(value(model.obj)))
model.y.pprint()