【发布时间】:2020-08-28 10:21:44
【问题描述】:
我的程序没有按照自己的意愿接受约束。
这是我的全部代码:
import sys
!{sys.executable} -m pip install pulp
import pulp
import pandas as pd
dates = [d.strftime('%Y-%m-%d') for d in pd.date_range("2020-01-01","2020-12-31")]
days = range(367)
preise = range(367)
capacity = 100000
#Decision variable
volumes = pulp.LpVariable.dicts("volumes", days,
lowBound=-2400,
upBound=1500,
cat=pulp.LpContinuous)
#Initialize Problem
storage = pulp.LpProblem("Storage Valuation", pulp.LpMaximize)
#Objective Function
storage += pulp.lpSum([volumes[(i)] * preise[(i)]
for i in days]), "objective function"
for j in days:
storage += sum(volumes) <= capacity, "capacity constraint {}".format(j)
storage.solve()
print("Status : ", pulp.LpStatus[storage.status])
print("Result : ", pulp.value(storage.objective))
data = []
for v in storage.variables():
data.append({'wert': v.varValue})
result = pd.DataFrame (data)
result.insert(1, "Storage level", result['wert'].cumsum(), True)
result.insert(2, "Date", dates, True)
with pd.option_context('display.max_rows', None, 'display.max_columns', None):
print(result)
我的决策变量的累计总和每天都不允许超过一定的容量。
对于约束,我也尝试过类似的东西:
for j in days:
storage += pulp.lpSum([volumes[i][j] for i in days) <= capacity, "Capacity Limit {}".format(j)
我认为 lpSum 语句有问题。 也许我的程序需要一个计数变量之类的东西。如果是这样,我该如何实现?
谢谢!
【问题讨论】:
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欢迎来到 SO!您能以minimal reproducible example 的形式提出您的问题吗?包括玩具示例数据和其他人需要的所有其他内容都可以点击运行,并查看您遇到的问题。您的约束在哪些方面未按预期运行?
标签: python optimization constraints linear-programming pulp