如何修复Pyomo中的‘ValueError: Constraint does not have a proper value’错误

ValueError: Constraint 'uvuoncea122222222222[1]' does not have a proper value. Found 'AbstractScalarConstraint'
Expecting a tuple or relational expression. Examples:
   sum(model.costs) == model.income
   (0, model.price[item], 50)

这是定义约束3时遇到的错误，以下是集合、决策变量定义及相关代码：

集合定义 #

## Sets
model.P = pe.Set(initialize = depots, ordered = False) #depots
model.S = pe.Set(initialize = satellites, ordered = False) #satellites
model.I = pe.Set(within=model.P | model.S) #union depots and satellites
model.Z = pe.Set(initialize = customers, ordered = False) #customers
model.Y = pe.Set(within=model.S | model.Z) #union customers and satellites
model.T = pe.Set(initialize=numUV, ordered=False) #FE vehicle
model.F = pe.Set(initialize=numCF, ordered=False) #SE vehicle
model.V = model.P | model.S | model.Z
model.A = model.V*model.V

决策变量定义 #

## Decision variables
model.x = pe.Var(model.T, model.P, model.S, domain = pe.NonNegativeIntegers) #flow FE
model.r = pe.Var(model.T, model.P, model.S, domain = pe.Binary) #binary FE arc used
model.q = pe.Var(model.F, model.S, model.Z, domain = pe.Binary) #binary SE arc used
model.w = pe.Var(model.Z, model.S, domain = pe.Binary) #binary Z gekoppeld aan S
model.u1 = pe.Var(model.T, domain = pe.Binary) #binary FE vehicle used
model.u2 = pe.Var(model.F, domain = pe.Binary) #binary SE vehicle used
model.p1 = pe.Var(model.T, model.S,domain = pe.NonNegativeIntegers) #arrival time at s
model.b1 = pe.Var(model.F, model.Z, domain = pe.NonNegativeIntegers) #arrival time at z
#model.pi = pe.Var(model.F, domain = pe.NonNegativeIntegers) #working duration
model.pprint()

目标函数 #

## Objective function
objExpr = (sum(model.r[t,i,j]* c[i,j] * cKm for t in model.T for i in model.I for j in model.I)\
          + sum(model.q[f,i,j]* c[i,j] * cKm for f in model.F for i in model.Y for j in model.Y)\
          + sum(model.u1[t]* ch1 for t in model.T) + sum(model.u2[f] * ch2 for f in model.F))
model.obj = pe.Objective(expr = objExpr, sense = pe.minimize)

约束定义 #

## Constraints
#2
model.confcfe = pe.ConstraintList()
for j in model.I:
    for t in model.T:
        expression = sum(model.r[t,l,j] for l in model.I) - sum(model.r[t,j,l] for l in model.I) == 0
        model.confcfe.add(expression)
#3
model.uvuoncea122222222222 = pe.ConstraintList()
for t in model.T:
    expression = sum(model.r[t, i, j] for i in model.I for j in model.P)
    constraint = pe.Constraint(expr=expression <= 1)
    model.uvuoncea122222222222.add(constraint)

我用不同于约束2的方式编写约束3，是因为之前写约束3会出现布尔值相关错误，原以为此写法能解决问题。尝试过多种约束定义方式（如约束规则、直接/间接添加到模型、范围约束等），但均无法解决该错误。

问题解决 #

错误核心原因是**ConstraintList.add()方法只接受关系表达式（如sum(...) <= 1），不能传入已经实例化的pe.Constraint对象**。你在约束3里先创建pe.Constraint实例再添加到列表，违背了ConstraintList的使用逻辑。

修改约束3的代码，直接将关系表达式传入add()即可：

#3 修改后的代码
model.uvuoncea122222222222 = pe.ConstraintList()
for t in model.T:
    expression = sum(model.r[t, i, j] for i in model.I for j in model.P) <= 1
    model.uvuoncea122222222222.add(expression)

另外需要注意：model.r定义的维度是(model.T, model.P, model.S)，但你在约束3中使用model.r[t,i,j]时，i属于model.I（P|S），j属于model.P，这会导致当i是S中的元素时，访问model.r[t,S,P]超出变量定义的索引范围（原变量r的第二个索引只能是P，第三个是S），这大概率是之前布尔值错误的根源。请确认约束逻辑是否正确，或调整model.r的定义维度。

内容的提问来源于stack exchange，提问作者Wieger Prinsze