我的程序是 不依不饶.
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)
我的决策变量的累积总和 在每天都不允许超过一定的容量。
对于约束条件,我也试过类似的东西。
for j in days:
storage += pulp.lpSum([volumes[i][j] for i in days) <= capacity, "Capacity Limit {}".format(j)
我相信lpSum语句有问题。也许我的程序需要一个类似计数变量的东西。如果是这样,我该如何实现?
谢谢你!我的程序没有采取我的约束条件。
下面的修改给出了一个结果(虽然我不太确定这是否是你需要的)。
#days = range(367)
#preise = range(367)
days = range(366)
preise = range(366)
改变约束条件(限制累计总和):
#for j in days:
# storage += sum(volumes) <= capacity, "capacity constraint {}".format(j)
for j in days:
storage += pulp.lpSum([volumes[(i)] for i in range(j+1)]) <= capacity
不要在字典上循环,变量的顺序不能保证。相反。
#for v in storage.variables():
# data.append({'wert': v.varValue})
for j in days:
data.append({'wert': volumes[(j)].varValue})