AttributeError: 'list' object has no attribute 'is_expression_type', What does this mean in pyomo?

model = pyo.ConcreteModel()


# Sets
model.k = pyo.RangeSet(136)
model.i = pyo.Set(initialize = [1,2,3,4])
model.n = pyo.Set(model.i,initialize = {1:[1,2,3],2:[1,2,3,4,5],3:[1,2,3],4:[1,2]})

def set_init(model):
    return [(i,n) for i in model.i for n in model.n[i]]
model.x = pyo.Set(dimen = 2,initialize = set_init)

#Param
model.t = pyo.Param(model.k,initialize = np.arange(0, 68, 0.5).tolist())
model.tauB = pyo.Param(model.x)

#Var
model.Sb = pyo.Var(model.k,model.x,within=pyo.Binary)
model.Db = pyo.Var(model.x,domain = pyo.NonNegativeReals)

def rule3(model,i,n):
    return model.Db[i,n]>=sum(model.Sb[k,i,n]*model.t[k] for k in model.k) - model.tauB[i,n]
model.objconst = pyo.Constraint(model.i,model.n[i],rule=rule3)

ERROR: Rule failed when generating expression for Constraint objconst with index (1, 1): AttributeError: 'list' object has no attribute 'is_expression_type'

ERROR: Constructing component 'objconst' from data=None failed: AttributeError: 'list' object has no attribute 'is_expression_type'

What is the correct way to use this indexed set model.x to build the constraint?

Solution

This should get you going. Made several tweaks. You should use model.x for creating your last constraint as you cannot reference the value i in the rule statement. Also, I re-worked your k values. This compiles.

import pyomo.environ as pyo
import numpy as np
model = pyo.ConcreteModel()

k_data = { idx:item for idx, item in enumerate(np.arange(0, 68, 0.5))}


# Sets
model.k = pyo.Set(initialize=k_data.keys())
model.i = pyo.Set(initialize = [1,2,3,4])
model.n = pyo.Set(model.i,initialize = {1:[1,2,3],2:[1,2,3,4,5],3:[1,2,3],4:[1,2]})

def set_init(model):
    return [(i,n) for i in model.i for n in model.n[i]]
model.x = pyo.Set(dimen = 2,initialize = set_init)

#Param
model.t = pyo.Param(model.k,initialize = k_data)
model.tauB = pyo.Param(model.x, initialize = 0)  # <-- need some values for this

#Var
model.Sb = pyo.Var(model.k,model.x,within=pyo.Binary)
model.Db = pyo.Var(model.x,domain = pyo.NonNegativeReals)

def rule3(model,i,n):
    return model.Db[i,n]>=sum(model.Sb[k,i,n]*model.t[k] for k in model.k) - model.tauB[i,n]
model.objconst = pyo.Constraint(model.x,rule=rule3)