Pyomo Abstract model "Empty constraint block written in LP format - solver may error"

Question

My pyomo abstract model has 2 sets with 3 parameters for each set.

I am minimizing the objective function with 4 constraints as follows:

from pyomo.environ import*
model=AbstractModel() # Model Creation

model.SUPPLIES=Set()  #Sets
model.DEMANDS=Set()


model.ccpu=Param(model.SUPPLIES)  #Parameters
model.csto=Param(model.SUPPLIES)
model.cmem=Param(model.SUPPLIES)
model.dcpu=Param(model.DEMANDS)
model.dsto=Param(model.DEMANDS)
model.dmem=Param(model.DEMANDS)

model.x=Var(model.SUPPLIES, model.DEMANDS, domain=Binary)  #Decision Variable

def objective_rule(model): #Objective Functions
    return sum(model.x[i,j]*model.dcpu[j] + model.x[i,j]*model.dmem[j] 
+model.x[i,j]*model.dsto[j] for i in model.SUPPLIES for j in model.DEMANDS)
model.mincost=Objective(rule=objective_rule, sense=minimize)

def cpu_rule(model, i): #Constraints
    return sum(model.x[i,j]*model.dcpu[j] for j in model.DEMANDS)<=model.ccpu[i]
const1=Constraint(model.SUPPLIES, rule=cpu_rule)

def mem_rule(model, i):
    return sum(model.x[i,j]*model.dmem[j] for j in model.DEMANDS)<=model.cmem[i]
const2=Constraint(model.SUPPLIES, rule=mem_rule)

def sto_rule(model, i):
    return sum(model.x[i,j]*model.dsto[j] for j in model.DEMANDS)<=model.csto[i]
const3=Constraint(model.SUPPLIES, rule=sto_rule)

def x_rule(model,j):
    return sum(model.x[i,j] for i in model.SUPPLIES)<=1
const4=Constraint(model.DEMANDS, rule=x_rule)


data=DataPortal() #Instance Creation and Solving
data.load(filename='transportationtry.dat', model=model)
instance = model.create_instance(data)
optimizer=SolverFactory("glpk")
optimizer.solve(instance)
instance.display()

The "transportationtry.dat" consist of the following data:

set SUPPLIES := P1 P2 P3;

set DEMANDS := C1 C2 C3 C4;

param: SUPPLIES: ccpu:= 

P1 35

P2 50

P3 40;

param: DEMANDS: dcpu:=

C1 1

C2 20

C3 5

C4 3;

param: SUPPLIES: csto:=

P1 35

P2 50

P3 40;

param: DEMANDS: dsto:=

C1 10

C2 2

C3 10

C4 3;

param: SUPPLIES: cmem:=

P1 35

P2 50

P3 40;

param: DEMANDS: dmem:=

C1 1

C2 2

C3 5

C4 3;

Answer 1

You need to attach the Constraint objects to the model you are building (otherwise they are not part of the model):

Instead of

const1 = Constraint(#...
    )

you need to do

model.const1 = Constraint(#...
    )