我的纸浆（线性规划批量）代码中不断出现错误，怎么了？

Question

我需要用线性规划分析一个批量问题，但我的纸浆代码不能正常工作

from pulp import *

prob = LpProblem("Lot_Sizing_Problem", LpMinimize)

period = []
for i in range(H):
    period.append(i)

order = LpVariable.dicts('order', period, lowBound = 0, upBound = 1, cat='integer'),
orderamount = LpVariable.dicts('orderamount', period, lowBound = 0, cat='integer'),
inventory = LpVariable.dicts('orderamount', period, lowBound = 0, cat='integer'),

prob += lpSum([A*period[i]+h*(inventory[i]+orderamount[i]-D[i]) for i in period])

prob += (inventory[i+1] for i in period) == inventory[i]+orderamount[i]-D[i]
prob += (orderamount[i] for i in period) <= M*order[i]
prob += (orderamount[i] for i in period) == D[i] - inventory[i]

prob.solve()

我不断地发现这个错误： TypeError:不支持+：“dict”和“dict”的操作数类型

以下是一些要输入的示例值，结果应为102.0： 以下是这些值的含义：（时间范围：H，持有成本：H，固定设置 成本：A，生产能力：C，需求清单：D，大M:M）

H=10
h=0.5
A=10
C=18
D=[12,10,13,14,13,15,17,20,19,14]
M=C

谢谢

Answer 1

有不少错误

from pulp import *

prob = LpProblem("Lot_Sizing_Problem", LpMinimize)

H=10
h=0.5
A=10
C=18
D=[12,10,13,14,13,15,17,20,19,14]
M=100

period = list(range(H))

order = LpVariable.dicts('order', period, lowBound = 0, upBound = 1, cat='integer')
orderamount = LpVariable.dicts('orderamount', period, lowBound = 0, cat='integer')
inventory = LpVariable.dicts('inventory', period, lowBound = 0, cat='integer')

prob += lpSum([A*period[i]+h*(inventory[i]+orderamount[i]-D[i]) for i in period])

for i in period:
  if i<H-1:
    prob += inventory[i+1]  == inventory[i]+orderamount[i]-D[i]
  prob += orderamount[i]  <= M*order[i]
  prob += orderamount[i]  == D[i] - inventory[i]

prob.solve()

请注意，使用dict进行整数索引不是一种正常的方法。所以，我可能会写：

order = [LpVariable(...) for i in period]

等等