如何在类中使用Pyomo装饰器

Question

下面是使用装饰器语法的简单Pyomo脚本-我想了解如何在类内使用此语法-在这种情况下，在Model内部。

无类版本

from pyomo.environ import *

import random

random.seed(1000)

model = AbstractModel()

model.N = Param(within=PositiveIntegers)
model.P = Param(within=RangeSet(1, model.N))
model.M = Param(within=PositiveIntegers)

model.Locations = RangeSet(1, model.N)
model.Customers = RangeSet(1, model.M)

model.d = Param(
    model.Locations,
    model.Customers,
    initialize=lambda n, m, model: random.uniform(1.0, 2.0),
    within=Reals,
)

model.x = Var(model.Locations, model.Customers, bounds=(0.0, 1.0))
model.y = Var(model.Locations, within=Binary)


@model.Objective()
def obj(model):
    return sum(
        model.d[n, m] * model.x[n, m] for n in model.Locations for m in model.Customers
    )


@model.Constraint(model.Customers)
def single_x(model, m):
    return (sum(model.x[n, m] for n in model.Locations), 1.0)


@model.Constraint(model.Locations, model.Customers)
def bound_y(model, n, m):
    return model.x[n, m] - model.y[n] <= 0.0


@model.Constraint()
def num_facilities(model):
    return sum(model.y[n] for n in model.Locations) == model.P

无法使用的类中的装饰器版本：

from pyomo.environ import *

import random

random.seed(1000)


class Model:
    def __init__(self):
        self.model = AbstractModel()

        self.model.N = Param(within=PositiveIntegers)
        self.model.P = Param(within=RangeSet(1, self.model.N))
        self.model.M = Param(within=PositiveIntegers)

        self.model.Locations = RangeSet(1, self.model.N)
        self.model.Customers = RangeSet(1, self.model.M)

        self.model.d = Param(
            self.model.Locations,
            self.model.Customers,
            initialize=lambda n, m, model: random.uniform(1.0, 2.0),
            within=Reals,
        )

        self.model.x = Var(
            self.model.Locations, self.model.Customers, bounds=(0.0, 1.0)
        )
        self.model.y = Var(self.model.Locations, within=Binary)

    @model.Objective()
    def obj(model):
        return sum(
            model.d[n, m] * model.x[n, m]
            for n in model.Locations
            for m in model.Customers
        )

    @model.Constraint(model.Customers)
    def single_x(model, m):
        return (sum(model.x[n, m] for n in model.Locations), 1.0)

    @model.Constraint(model.Locations, model.Customers)
    def bound_y(model, n, m):
        return model.x[n, m] - model.y[n] <= 0.0

    @model.Constraint()
    def num_facilities(model):
        return sum(model.y[n] for n in model.Locations) == model.P

Answer 1

我无能为力，只有几个问题：

• 您是否知道在某处记录了@ model.Objective（）的使用（与Constraint等相同）？我不知道它的存在，而且很棒[]
• 您为什么希望您的“功能规则”成为课程的方法
？您无法将它们定义为__init__方法中的函数吗？

我想我首先缺少的是使用类的好处。如果您只是想以某种方式包装模型构造，那么更好的方法是使用函数：

def create_model():
    model = AbstractModel()

    ...

    @model.Constraint()
    def some_rule_function(model):
        ...

    ...

    return model
然后您可以让您的课程Model刚刚在构造中收到抽象模型：

class Model:
    def __init__(self, model):
         self.model = model

    # other behavior you want to add to the class
示例用法：

model = Model(create_model())