Pyomo：如何将None作为参数值传递

Question

这是一个很容易回答的问题。我试图创建一个模型，允许用户为参数值传递None。这样他们就可以定义上限/下限，或者选择不设上限。集合/参数定义、AMPL样式数据文件部分和约束函数的示例问题（饮食问题）如下所示：

设置/参数定义

model.Ingredients = pyo.Set()
model.Properties = pyo.Set()
model.IngredientProperties = pyo.Param(model.Ingredients, model.Properties)
model.MinProperty = pyo.Param(model.Properties, within=pyo.Any)
model.MaxProperty = pyo.Param(model.Properties, within=pyo.Any)

数据文件部分

set Ingredients := Banana Milk Yogurt ;
set Properties := Fat Protein Carbs ;
param:  MinProperty  MaxProperty :=
      Fat  0.009       0.013
  Protein  0.200        None
    Carbs   None       0.070;
param IngredientProperties:    Fat    Protein  Carbs :=
                    Banana    0.375    0.020   0.010
                      Milk    0.003    0.075   0.015
                    Yogurt    0.015    0.650   0.075;

约束功能

def _property_constraint_rule(model, p):
    return (model.MinProperty[p], sum(
        model.IngredientProperties[i, p]
        * model.Blend[i]
        for i in model.Ingredients
        ), model.MaxProperty[p])

不幸的是，当我尝试此操作时，会收到错误消息：TypeError: Cannot treat the value 'None' as a constant.是否有其他方法将参数定义为无？我知道我可以使用大量的正数/负数，但必须有更好的方法

Answer 1

如果您要继续使用抽象模型，我认为您必须使用默认值，这很好。如果使用的是具体模型，则可以有条件地构造约束，因为数据在构造时是已知的

此外，在数据文件中，需要将此格式中的None值表示为句点.。如果使用“None”这个词，它会呕吐，因为它不会被识别为Python的None

这个试用版对我来说很好

import pyomo.environ as pyo

model = pyo.AbstractModel()

model.Ingredients = pyo.Set()
model.Properties = pyo.Set()
model.IngredientProperties = pyo.Param(model.Ingredients, model.Properties)
model.MinProperty = pyo.Param(model.Properties, within=pyo.Any, default=0.0)
model.MaxProperty = pyo.Param(model.Properties, within=pyo.Any, default=100)

model.Blend = pyo.Var(model.Ingredients, domain=pyo.NonNegativeReals)


def _property_constraint_rule(model, p):
    return (model.MinProperty[p], sum(
        model.IngredientProperties[i, p] * model.Blend[i]
        for i in model.Ingredients), model.MaxProperty[p])
model.c1 = pyo.Constraint(model.Properties, rule=_property_constraint_rule)

data = pyo.DataPortal()
data.load(filename='data.dat')

instance = model.create_instance(data)

instance.pprint()

产量：

3 Set Declarations
    IngredientProperties_index : Dim=0, Dimen=2, Size=9, Domain=None, Ordered=False, Bounds=None
        Virtual
    Ingredients : Dim=0, Dimen=1, Size=3, Domain=None, Ordered=False, Bounds=None
        ['Banana', 'Milk', 'Yogurt']
    Properties : Dim=0, Dimen=1, Size=3, Domain=None, Ordered=False, Bounds=None
        ['Carbs', 'Fat', 'Protein']

3 Param Declarations
    IngredientProperties : Size=9, Index=IngredientProperties_index, Domain=Any, Default=None, Mutable=False
        Key                   : Value
          ('Banana', 'Carbs') :  0.01
            ('Banana', 'Fat') : 0.375
        ('Banana', 'Protein') :  0.02
            ('Milk', 'Carbs') : 0.015
              ('Milk', 'Fat') : 0.003
          ('Milk', 'Protein') : 0.075
          ('Yogurt', 'Carbs') : 0.075
            ('Yogurt', 'Fat') : 0.015
        ('Yogurt', 'Protein') :  0.65
    MaxProperty : Size=3, Index=Properties, Domain=Any, Default=100, Mutable=False
        Key   : Value
        Carbs :  0.07
          Fat : 0.013
    MinProperty : Size=3, Index=Properties, Domain=Any, Default=0.0, Mutable=False
        Key     : Value
            Fat : 0.009
        Protein :   0.2

1 Var Declarations
    Blend : Size=3, Index=Ingredients
        Key    : Lower : Value : Upper : Fixed : Stale : Domain
        Banana :     0 :  None :  None : False :  True : NonNegativeReals
          Milk :     0 :  None :  None : False :  True : NonNegativeReals
        Yogurt :     0 :  None :  None : False :  True : NonNegativeReals

1 Constraint Declarations
    c1 : Size=3, Index=Properties, Active=True
        Key     : Lower : Body                                                          : Upper : Active
          Carbs :   0.0 :  0.01*Blend[Banana] + 0.015*Blend[Milk] + 0.075*Blend[Yogurt] :  0.07 :   True
            Fat : 0.009 : 0.375*Blend[Banana] + 0.003*Blend[Milk] + 0.015*Blend[Yogurt] : 0.013 :   True
        Protein :   0.2 :   0.02*Blend[Banana] + 0.075*Blend[Milk] + 0.65*Blend[Yogurt] : 100.0 :   True

8 Declarations: Ingredients Properties IngredientProperties_index IngredientProperties MinProperty MaxProperty Blend c1

修改的data.dat

set Ingredients := Banana Milk Yogurt ;
set Properties := Fat Protein Carbs ;
param:  MinProperty  MaxProperty :=
      Fat  0.009        0.013
  Protein  0.200        .
    Carbs  .            0.070;
param IngredientProperties:    Fat    Protein  Carbs :=
                    Banana    0.375    0.020   0.010
                      Milk    0.003    0.075   0.015
                    Yogurt    0.015    0.650   0.075;