Error , Infeasible No value for uninitialized NumericValue object

[John Icare]

I'm trying to optmize a problem of clients/facility allocation and I'm  using pyomo to do so. I have the following problem that appear and cannot solve it even if I initialize all the values of Model.z to 0; the
problems is still infeasible 

I got this error whatever I try and I don't understand why Z should be initialized as it is the variable I'm trying to minimize 

from __future__ import division
import pyomo.environ as pyo
#from pyomo.environ import *
from pyomo.opt import SolverFactory
import sys
import numpy as np
import sys
import os

from time import perf_counter
from pulp import *
from pyomo.util.infeasible import log_infeasible_constraints

#print(sys.path)
opt = pyo.SolverFactory('glpk')
opt.options['threads'] =4


#import instance 
model = pyo.ConcreteModel()

# n is the number of facility related to J
# m is the number of clients related to I 
# t is the number of periods relatdd to T 
# H is the maximum number of clients that can be served

[m,n,t,H] = np.genfromtxt(fname = r'./Instances/data-100-10-4-3-0.txt', dtype = None, max_rows = 1)
f_values = np.genfromtxt(fname = r'./Instances/data-100-10-4-3-0.txt', dtype = None, max_rows = 4,skip_header=1)
c_values = np.genfromtxt(fname = r'./Instances/data-100-10-4-3-0.txt', dtype = None, skip_footer = 1,skip_header=5)
p_values = np.genfromtxt(fname = r'./Instances/data-100-10-4-3-0.txt', dtype = None, skip_header=405)


model.J = pyo.Set(initialize=[int(i)+1 for i in range(n)])
model.T= pyo.Set(initialize=[int(i)+1 for i in range(t)])
model.T.pprint()
model.I = pyo.Set(initialize=[int(i)+1 for i in range(m)])
model.H = pyo.Set(initialize=[int(i)+1 for i in range(H)])

# Generation of Subsets of all clients

client_list = [int(i)+1 for i in range(100)] 
list_H = [int(i)+1 for i in range(H)]
possible_groups_of_clients=[]
for i in list_H:
    possible_groups_of_clients += [list(elem) for elem in itertools.combinations(client_list,i)]

possible_groups_of_clients = possible_groups_of_clients[0:5] #Only select the first 5 subsets


model.K = pyo.Set(initialize=[int(i)+1 for i in range(len(possible_groups_of_clients))])

p_val = np.zeros((len(model.K),len(model.J),len(model.T))) 


for t in model.T: 
    t=t-1 #Pyomo starts at 1
    for j in model.J:
        j=j-1
        count = 0
        for k in possible_groups_of_clients:

            #k=k+1
            c_sum=0;
            for p in k:
                if t==0: 
                    c_sum = c_sum +c_values[p][j]
                elif t==1: 
                    c_sum = c_sum +c_values[p+100][j]
                elif t==2: 
                    c_sum = c_sum +c_values[p+200][j]
                elif t==3:
                    c_sum = c_sum +c_values[p+300][j]
            #print(f_values[t][j])


            p_val[count][j][t] = f_values[t][j]+ c_sum
            count=count+1


model.p_val = pyo.Param(model.K,model.J,model.T, initialize = lambda model,k,j,t: p_val[k-1][j-1][t-1])

#Matrice Aik 

A = [[0 for k in range(len(possible_groups_of_clients))]  for i in range(100)]
#model.p_val = pyo.Param(model.T,model.J,model.K, initialize = lambda model,t,j,k: A[t-1][j-1][k-1])
model.A = pyo.Param(model.I, model.K, mutable= True,initialize= lambda model,i,k: A[i-1][k-1])

count=1
for i in possible_groups_of_clients:

    for k in range(100):
        k=k+1
        #print(k)
        if k in i: 
            model.A[k,count]=1
        else: 
            model.A[k,count]=0

    count=count+1

model.z = pyo.Var(model.K,model.J,model.T,initialize= 0,within=pyo.NonNegativeReals,bounds=(0,1))



a=range(len(possible_groups_of_clients))
print(p_values)

# Minization of objective functions



# Constraint unique client
model.uniq_client = pyo.Constraint(
        model.I,
        rule=lambda model, i: sum(model.A[i,k]*model.z[k,j,t] for t in model.T for j in model.J for k in model.K) == 1
    )
model.unique_service_groupclients = pyo.Constraint(
       model.J, model.T,
        rule=lambda model,j,t: sum(model.z[k,j,t] for k in model.K)<=1
    )

model.min_factory_perperiod = pyo.Constraint(
        model.T,
        rule=lambda model, t: sum(model.z[k,j,t] for j in model.J for k in model.K )>=p_values[t-1]
    )



model.obj = pyo.Objective(rule= lambda model:sum(model.p_val[k,j,t]*model.z[k,j,t] for t in model.T  for j in model.J for k in model.K ), sense= pyo.minimize)
model.pprint()




sol = pyo.SolverFactory('glpk',).solve(model).write()

log_infeasible_constraints(model)


# ==========================================================
# = Solver Results                                         =
# ==========================================================
# ----------------------------------------------------------
#   Problem Information
# ----------------------------------------------------------
Problem: 
- Name: unknown
  Lower bound: -inf
  Upper bound: inf
  Number of objectives: 1
  Number of constraints: 145
  Number of variables: 201
  Number of nonzeros: 601
  Sense: minimize



# ----------------------------------------------------------
#   Solver Information
# ----------------------------------------------------------
Solver: 
- Status: ok
  Termination condition: infeasible
  Statistics: 
    Branch and bound: 
      Number of bounded subproblems: 0
      Number of created subproblems: 0
  Error rc: 0
  Time: 0.008042335510253906
ERROR: evaluating object as numeric value: z[1,1,1]
    (object: <class 'pyomo.core.base.var._GeneralVarData'>)
    No value for uninitialized NumericValue object z[1,1,1]
ERROR: evaluating object as numeric value: 1.0 - (A[1,1]*z[1,1,1] +
A[1,2]*z[2,1,1] + A[1,3]*z[3,1,1] + A[1,4]*z[4,1,1] + A[1,5]*z[5,1,1] +
A[1,1]*z[1,2,1] + A[1,2]*z[2,2,1] + A[1,3]*z[3,2,1] + A[1,4]*z[4,2,1] +
A[1,5]*z[5,2,1] + A[1,1]*z[1,3,1] + A[1,2]*z[2,3,1] + A[1,3]*z[3,3,1] +
A[1,4]*z[4,3,1] + A[1,5]*z[5,3,1] + A[1,1]*z[1,4,1] + A[1,2]*z[2,4,1] +
A[1,3]*z[3,4,1] + A[1,4]*z[4,4,1] + A[1,5]*z[5,4,1] + A[1,1]*z[1,5,1] +
A[1,2]*z[2,5,1] + A[1,3]*z[3,5,1] + A[1,4]*z[4,5,1] + A[1,5]*z[5,5,1] +
A[1,1]*z[1,6,1] + A[1,2]*z[2,6,1] + A[1,3]*z[3,6,1] + A[1,4]*z[4,6,1] +
A[1,5]*z[5,6,1] + A[1,1]*z[1,7,1] + A[1,2]*z[2,7,1] + A[1,3]*z[3,7,1] +
A[1,4]*z[4,7,1] + A[1,5]*z[5,7,1] + A[1,1]*z[1,8,1] + A[1,2]*z[2,8,1] +
A[1,3]*z[3,8,1] + A[1,4]*z[4,8,1] + A[1,5]*z[5,8,1] + A[1,1]*z[1,9,1] +
A[1,2]*z[2,9,1] + A[1,3]*z[3,9,1] + A[1,4]*z[4,9,1] + A[1,5]*z[5,9,1] +
A[1,1]*z[1,10,1] + A[1,2]*z[2,10,1] + A[1,3]*z[3,10,1] + A[1,4]*z[4,10,1]
+ A[1,5]*z[5,10,1] + A[1,1]*z[1,1,2] + A[1,2]*z[2,1,2] + A[1,3]*z[3,1,2] +
A[1,4]*z[4,1,2] + A[1,5]*z[5,1,2] + A[1,1]*z[1,2,2] + A[1,2]*z[2,2,2] +
A[1,3]*z[3,2,2] + A[1,4]*z[4,2,2] + A[1,5]*z[5,2,2] + A[1,1]*z[1,3,2] +
A[1,2]*z[2,3,2] + A[1,3]*z[3,3,2] + A[1,4]*z[4,3,2] + A[1,5]*z[5,3,2] +
A[1,1]*z[1,4,2] + A[1,2]*z[2,4,2] + A[1,3]*z[3,4,2] + A[1,4]*z[4,4,2] +
A[1,5]*z[5,4,2] + A[1,1]*z[1,5,2] + A[1,2]*z[2,5,2] + A[1,3]*z[3,5,2] +
A[1,4]*z[4,5,2] + A[1,5]*z[5,5,2] + A[1,1]*z[1,6,2] + A[1,2]*z[2,6,2] +
A[1,3]*z[3,6,2] + A[1,4]*z[4,6,2] + A[1,5]*z[5,6,2] + A[1,1]*z[1,7,2] +
A[1,2]*z[2,7,2] + A[1,3]*z[3,7,2] + A[1,4]*z[4,7,2] + A[1,5]*z[5,7,2] +
A[1,1]*z[1,8,2] + A[1,2]*z[2,8,2] + A[1,3]*z[3,8,2] + A[1,4]*z[4,8,2] +
A[1,5]*z[5,8,2] + A[1,1]*z[1,9,2] + A[1,2]*z[2,9,2] + A[1,3]*z[3,9,2] +
A[1,4]*z[4,9,2] + A[1,5]*z[5,9,2] + A[1,1]*z[1,10,2] + A[1,2]*z[2,10,2] +
A[1,3]*z[3,10,2] + A[1,4]*z[4,10,2] + A[1,5]*z[5,10,2] + A[1,1]*z[1,1,3] +
A[1,2]*z[2,1,3] + A[1,3]*z[3,1,3] + A[1,4]*z[4,1,3] + A[1,5]*z[5,1,3] +
A[1,1]*z[1,2,3] + A[1,2]*z[2,2,3] + A[1,3]*z[3,2,3] + A[1,4]*z[4,2,3] +
A[1,5]*z[5,2,3] + A[1,1]*z[1,3,3] + A[1,2]*z[2,3,3] + A[1,3]*z[3,3,3] +
A[1,4]*z[4,3,3] + A[1,5]*z[5,3,3] + A[1,1]*z[1,4,3] + A[1,2]*z[2,4,3] +
A[1,3]*z[3,4,3] + A[1,4]*z[4,4,3] + A[1,5]*z[5,4,3] + A[1,1]*z[1,5,3] +
A[1,2]*z[2,5,3] + A[1,3]*z[3,5,3] + A[1,4]*z[4,5,3] + A[1,5]*z[5,5,3] +
A[1,1]*z[1,6,3] + A[1,2]*z[2,6,3] + A[1,3]*z[3,6,3] + A[1,4]*z[4,6,3] +
A[1,5]*z[5,6,3] + A[1,1]*z[1,7,3] + A[1,2]*z[2,7,3] + A[1,3]*z[3,7,3] +
A[1,4]*z[4,7,3] + A[1,5]*z[5,7,3] + A[1,1]*z[1,8,3] + A[1,2]*z[2,8,3] +
A[1,3]*z[3,8,3] + A[1,4]*z[4,8,3] + A[1,5]*z[5,8,3] + A[1,1]*z[1,9,3] +
A[1,2]*z[2,9,3] + A[1,3]*z[3,9,3] + A[1,4]*z[4,9,3] + A[1,5]*z[5,9,3] +
A[1,1]*z[1,10,3] + A[1,2]*z[2,10,3] + A[1,3]*z[3,10,3] + A[1,4]*z[4,10,3]
+ A[1,5]*z[5,10,3] + A[1,1]*z[1,1,4] + A[1,2]*z[2,1,4] + A[1,3]*z[3,1,4] +
A[1,4]*z[4,1,4] + A[1,5]*z[5,1,4] + A[1,1]*z[1,2,4] + A[1,2]*z[2,2,4] +
A[1,3]*z[3,2,4] + A[1,4]*z[4,2,4] + A[1,5]*z[5,2,4] + A[1,1]*z[1,3,4] +
A[1,2]*z[2,3,4] + A[1,3]*z[3,3,4] + A[1,4]*z[4,3,4] + A[1,5]*z[5,3,4] +
A[1,1]*z[1,4,4] + A[1,2]*z[2,4,4] + A[1,3]*z[3,4,4] + A[1,4]*z[4,4,4] +
A[1,5]*z[5,4,4] + A[1,1]*z[1,5,4] + A[1,2]*z[2,5,4] + A[1,3]*z[3,5,4] +
A[1,4]*z[4,5,4] + A[1,5]*z[5,5,4] + A[1,1]*z[1,6,4] + A[1,2]*z[2,6,4] +
A[1,3]*z[3,6,4] + A[1,4]*z[4,6,4] + A[1,5]*z[5,6,4] + A[1,1]*z[1,7,4] +
A[1,2]*z[2,7,4] + A[1,3]*z[3,7,4] + A[1,4]*z[4,7,4] + A[1,5]*z[5,7,4] +
A[1,1]*z[1,8,4] + A[1,2]*z[2,8,4] + A[1,3]*z[3,8,4] + A[1,4]*z[4,8,4] +
A[1,5]*z[5,8,4] + A[1,1]*z[1,9,4] + A[1,2]*z[2,9,4] + A[1,3]*z[3,9,4] +
A[1,4]*z[4,9,4] + A[1,5]*z[5,9,4] + A[1,1]*z[1,10,4] + A[1,2]*z[2,10,4] +
A[1,3]*z[3,10,4] + A[1,4]*z[4,10,4] + A[1,5]*z[5,10,4])
        (object: <class 'pyomo.core.expr.numeric_expr.SumExpression'>)
    No value for uninitialized NumericValue object z[1,1,1]
Traceback (most recent call last):
  File "main.py", line 246, in <module>
    log_infeasible_constraints(model)
  File "/home/john/.local/lib/python3.6/site-packages/pyomo   /util/infeasible.py", line 25, in log_infeasible_constraints
    if constr.equality and fabs(value(constr.lower - constr.body)) >= tol:
  File "/home/john/.local/lib/python3.6/site-packages/pyomo/core/expr/numvalue.py", line 226, in value
    tmp = obj(exception=True)
  File "/home/john/.local/lib/python3.6/site-packages/pyomo/core/expr/numeric_expr.py", line 222, in __call__
    return evaluate_expression(self, exception)
  File "/home/john/.local/lib/python3.6/site-packages/pyomo/core/expr/visitor.py", line 973, in evaluate_expression
    return visitor.dfs_postorder_stack(exp)
  File "/home/john/.local/lib/python3.6/site-packages/pyomo/core/expr/visitor.py", line 518, in dfs_postorder_stack
flag, value = self.visiting_potential_leaf(_sub)
  File "/home/john/.local/lib/python3.6/site-packages/pyomo/core/expr/visitor.py", line 893, in visiting_potential_leaf
    return True, value(node)
  File "/home/john/.local/lib/python3.6/site-packages/pyomo/core/expr/numvalue.py", line 230, in value
% (obj.name,))
ValueError: No value for uninitialized NumericValue object z[1,1,1]

[Siirola, John D]

This mailing list is for discussing the development of the Pyomo code.  Please ask user / support questions on the pyomo-forum group.

 

Thank you,

john

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