如何求解错误检索组件索引索引[1]：尚未构造组件

Question

我正在遇到此错误（错误检索组件索引索引[1]：尚未构造组件。），我无法弄清楚下面的代码在哪里出错，我正在pyomo中编码一个线性程序，我没有精通Python，当我学习线性编程时，我基本上是在重复。你能帮我吗？错误似乎在定义目标函数的行中...请帮助

''

#!/usr/bin/env python3

- - 编码：UTF-8 - -

“”“” 在太阳上创建6月12日20:01:39 2022

@author：Israathiab ”“”

import pyomo.environ as pyo

def pyomoresults(QEMCAProfitModel): # define a function to print optimization results
""""Print results of the optimization of model 'QEMCAProfitModel' including 
objective value at optimum, optimal decision variable values and 
dual/slack information on constraints"""
print('')
print('=========================')
print('QEMCAProfitModel Maximization Solution')
print('=========================')
print('')
print('Objective Function Value at Optimum')
# loop over objective objects in the model
for f in QEMCAProfitModel.component_objects(pyo.Objective, active=True):
    print ('Objective', f) # print the name of the objective
    # loop over subobjectives (in this course we will only have one)
    for index in f: 
        print ('      ', index, pyo.value(f[index]))
print('')
print('Decision Variable Values at Optimum')
# loop over decision variable objects in model
for v in QEMCAProfitModel.component_objects(pyo.Var, active=True):
    print ('Variable', v) # print variable name
    for index in v: # loop over index of variable object
        # print index/optimal values
        print ('      ', index, pyo.value(v[index])) 
print('')
print ('Duals/Shadow Prices at Optimum')
# loop over constraint objects in model
for d in QEMCAProfitModel.component_objects(pyo.Constraint, active=True):
    print ('Constraint',d) # print constraint name
    for index in d: # loop over index of constraint object
        # print dual value of constraint
        print ('      ', index, QEMCAProfitModel.dual[d[index]]) 
print('')     
print ("Slack at Optimum")
# loop over constraint objects in model
for i in QEMCAProfitModel.component_objects(pyo.Constraint, active=True):
    print ("   Constraint",Ci) # print constraint name
    for index in Ci: # loop over index of constraint object
        # print constraint slack information
        print ("      ", index, Ci[index].lslack(), ' - ', Ci[index].uslack()) 


#Define Concrete model

QEMCAProfitModel = pyo.ConcreteModel

#Define variable dictionary for decision variable index 

#Crop index

I = [1,2,3,4,5,6]

#Define parameters

#Define mean profit per crop - ETB

mPi = {1:15635.2, 2:9571.36, 3:13392.6, 4:39834.6, 5:49074.1, 6:11365.6}

#Define mean cost per hectar of crop - ETB/Hecatre

Ci = {1:10467.37, 2:8160.47, 3:12392.22, 4:5702.01, 5:8265.88, 6:8514.31}

#Define objective function

QEMCAProfitModel.L = pyo.Var(I,within=pyo.NonNegativeReals)



QEMCAProfitModel.Profit = pyo.Objective(expr=sum(mPi[i] * QEMCAProfitModel.L[i] for i `in I), sense=pyo.maximize)`
#Profit un EBT

#Define constraints

def Budget_rule(QEMCAProfitModel, i):
return sum(Ci[i] * QEMCAProfitModel.L[i] for i in I) <= 850636 
QEMCAProfitModel.Budget_rule = pyo.Constraint(I, rule=Budget_rule)


def Land_rule(QEMCAProfitModel, i):
return sum(QEMCAProfitModel.L[i] for i in I) <= 47.77  
QEMCAProfitModel.Land_rule = pyo.Constraint(I, rule=Land_rule)

def Land_rule_min(QEMCAProfitModel, i):
return sum(QEMCAProfitModel.L[i] for i in I) >= 0  
QEMCAProfitModel.Land_rule_min = pyo.Constraint(I, rule=Land_rule_min)


def Consumption_rule_1(QEMCAProfitModel, i):
return 4560.64 * QEMCAProfitModel.L[1] >= 51250
QEMCAProfitModel.Consumption_rule_1 = pyo.Constraint(I, rule=Consumption_rule_1)

def Consumption_rule_2(QEMCAProfitModel, i):
return 5764.71 * QEMCAProfitModel.L[2] >= 36710
QEMCAProfitModel.Consumption_rule_2 = pyo.Constraint(I, rule=Consumption_rule_2)


def Consumption_rule_3(QEMCAProfitModel, i):
return 9908.3 * QEMCAProfitModel.L[3] >= 30316
QEMCAProfitModel.Consumption_rule_3 = pyo.Constraint(I, rule=Consumption_rule_3)


def Consumption_rule_4(QEMCAProfitModel, i):
return 16614.81 * QEMCAProfitModel.L[4] >= 4850
QEMCAProfitModel.Consumption_rule_4 = pyo.Constraint(I, rule=Consumption_rule_4)

def Consumption_rule_5(QEMCAProfitModel, i):
return 20323.81 * QEMCAProfitModel.L[5] >= 4450
QEMCAProfitModel.Consumption_rule_5 = pyo.Constraint(I, rule=Consumption_rule_5)

def Consumption_rule_6(QEMCAProfitModel, i):
return 4400 * QEMCAProfitModel.L[6] >= 7100
QEMCAProfitModel.Consumption_rule_6 = pyo.Constraint(I, rule=Consumption_rule_6)

QEMCAProfitModel.pprint()

QEMCAProfitModel.dual = pyo.Suffix(direction=pyo.Suffix.IMPORT)

opt = pyo.SolverFactory('glpk')

results = opt.solve(QEMCAProfitModel)

QEMCAProfitModel.display()

QEMCAProfitModel.dual.display()

pyomoresults(QEMCAProfitModel)

'''

Answer 1

定义模型对象时，您会缺少parens：

QEMCAProfitModel = pyo.ConcreteModel

应该

QEMCAProfitModel = pyo.ConcreteModel()

没有parens，qemcaprofitModel是 class concretemodel而不是类的实例。触发组件“构造”的“魔术”（setAttr __ block数据实例上的方法）仅在block> block instances（并且模型是一个块）上工作。

请注意，同一方法还负责将属性名称复制到组件名称。由于没有触发，因此您在错误消息中看到默认组件名称（类名称，indexedvar）。