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python - 纸浆优化错误 - LPVariable 对象不支持索引

问题描述

尝试添加位于第 31 行的约束时，我一直遇到错误，模型 += ([MAHL[i][j] for (i,j) in yearlyhours]) <= 40

我不确定如何正确设置此约束。我想说的是，在 i 和 j 的每个索引处，特定值需要小于 40，并对所有 i、j 对执行此操作。

我对 PULP 非常陌生，并试图启动并运行一个基本模型。输入数据只是一堆 365 行长和 24 列宽的随机值。

from pulp import *
import pandas as pd
import numpy as np
import xlrd

model = pulp.LpProblem("Basic Model", pulp.LpMaximize)

YPER = 365
HE = 24

yearlyhours = [(i,j) for i in range(YPER) for j in range(HE)]

xlsx = pd.ExcelFile('IvA.xlsx')
df1 = pd.read_excel(xlsx, 'Sheet5')
df2 = pd.read_excel(xlsx, 'Sheet3')
df3 = pd.read_excel(xlsx, 'Sheet2')

MAHL = pulp.LpVariable('MAHL', (YPER, HE), cat='Integer')
MALL = pulp.LpVariable('MALL', cat='Integer')
DAHL = pulp.LpVariable('DAHL', cat='Integer')
DALL = pulp.LpVariable('DALL', cat='Integer')

book = xlrd.open_workbook('IvA.xlsx')
sheet10 = book.sheet_by_name('Sheet10')
sheet11 = book.sheet_by_name('Sheet11')

DAPRICE = [[sheet10.cell_value(r, c) for c in range(sheet10.ncols)] for r in range(sheet10.nrows)]
LOAD = [[sheet11.cell_value(r, c) for c in range(sheet11.ncols)] for r in range(sheet11.nrows)]

#model += (MAHL[i][j] for i in range(YPER) for j in range(HE)) <= 40
model += ([MAHL[i][j] for (i,j) in yearlyhours]) <= 40

model += (pulp.lpSum([DAPRICE[i][j] * LOAD[i][j] for i in range(YPER) for j in range(HE)]))

model.solve()
pulp.LpStatus[model.status]
print("Status:", LpStatus[model.status])

obj = value(model.objective)
print(obj)

我尝试了一些解决方案，另外一个被注释掉了。

Traceback (most recent call last):
  File "bs.py", line 31, in <module>
    model += ([MAHL[i][j] for (i,j) in yearlyhours]) <= 40
  File "bs.py", line 31, in <listcomp>
    model += ([MAHL[i][j] for (i,j) in yearlyhours]) <= 40
TypeError: 'LpVariable' object does not support indexing

标签： pythonoptimizationpulp

解决方案

您已定义MAHL为 a pulp.LpVariable，它（如错误状态）不支持索引，因为它对 LP 变量进行建模。

您可能希望使用pulp.LpVariable.dicts.

例子：

MAHL = pulp.LpVariable.dicts('MAHL', yearlyhours, cat=pulp.LpInteger)

并将其称为

model += pulp.lpSum([MAHL[(i,j)] for (i,j) in yearlyhours]) <= 40

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