使用pyomo模型优化函数

Question

我对优化代码有一个问题。我写的代码应该优化这两个目标，考虑它们的表达式，并产生可以绘制的值。这是我的代码，如下所述。

  from pyomo.environ import *
  import numpy as np
  import pandas as pd
  import random
  import matplotlib.pyplot as plt

  model = ConcreteModel()

  st1 = []
  st2 = []

  rows =10
  n = []
  for i in range(rows):
     rn = random.randint(1,10)
     n.append(rn)
     print(rn)
     model.x1 = Var(within=NonNegativeReals, initialize=rn)
     model.x2 = Var(within=NonNegativeReals, initialize=rn) 
     model.x3 = Var(within=NonNegativeReals, initialize=rn)
     model.x4 = Var(within=NonNegativeReals, initialize=rn)

     model.f1 = Var()
     model.f2 = Var()
     model.C_f1 = Constraint(expr= model.f1 == 2 * model.x1 - model.x2 + 4 * model.x3 + model.x4)
     model.C_f2 = Constraint(expr= model.f2 == -3 * model.x1 + model.x2 + 2 * model.x3 - 2 * model.x4)
     model.O_f1 = Objective(expr= model.f1, sense=maximize)
     model.O_f2 = Objective(expr= model.f2, sense=maximize)

     model.O_f1.activate()
     model.O_f2.deactivate()
     solver = SolverFactory('glpk')
     solver.solve(model);

     print('( x1 , x2 , x3 , x4 ) = ( ' + str(value(model.x1)) + ' , ' + str(value(model.x2)) + ' , ' + str(value(model.x3)) + ' , ' + str(value(model.x4)) + ' )')
     st1.append(value(model.f1))
     st2.append(value(model.f2))

     model.O_f2.activate()
     model.O_f1.deactivate()

     solver = SolverFactory('glpk')
     solver.solve(model);

     print('( x1 , x2 , x3 , x4 ) = ( ' + str(value(model.x1)) + ' , ' + str(value(model.x2)) + ' , ' + str(value(model.x3)) + ' , ' + str(value(model.x4)) + ' )')
     st1.append(value(model.f1))
     st2.append(value(model.f2))

 print(n)

 print(st1)
 print(st2)


 plt.scatter(st1, st2)
 plt.xlabel('Objective A')
 plt.ylabel('Objective B')
 plt.show()

这就是出现的错误，

 7
( x1 , x2 , x3 , x4 ) = ( 7 , 7 , 7 , 7 )
ERROR: evaluating object as numeric value: f1
       (object: <class 'pyomo.core.base.var.ScalarVar'>)
   No value for uninitialized NumericValue object f1
---------------------------------------------------------------------------
 ValueError                                Traceback (most recent call last)
 <ipython-input-14-c6162a718dc9> in <module>
     34 
     35     print('( x1 , x2 , x3 , x4 ) = ( ' + str(value(model.x1)) + ' , ' + 
     str(value(model.x2)) + ' , ' + str(value(model.x3)) + ' , ' + str(value(model.x4)) + ' )')
     ---> 36     st1.append(value(model.f1))
     37     st2.append(value(model.f2))
     38 

     pyomo\core\expr\numvalue.pyx in pyomo.core.expr.numvalue.value()

     pyomo\core\expr\numvalue.pyx in pyomo.core.expr.numvalue.value()

     ValueError: No value for uninitialized NumericValue object f1

有没有人可以帮我解决这个问题，给我看看错误，或者帮我找一个替代方案

Answer 1

问题是你的模型是无界的。您正在尝试最大化它，并且没有上限约束，因此值可以是无限的。

应始终在解算后首先检查解算器状态，以便在深入研究之前查看所获得的结果。添加以下内容：

result = solver.solve(model);
print(result)