我正在尝试在纸浆中自动化模型定义。 现在,我有以下模型:
import pulp as pl
" Cost parameters"
p1 = 200 # Cost per unit 1
p2 = 300 # Cost per unit 2
" VARIABLES"
k0101 = pl.LpVariable("k0101", 0, 1, pl.LpInteger)
k0102 = pl.LpVariable("k0102", 0, 1, pl.LpInteger)
k0201 = pl.LpVariable("k0201", 0, 1, pl.LpInteger)
k0202 = pl.LpVariable("k0202", 0, 1, pl.LpInteger)
###### DEMAND
x010101 = pl.LpVariable("x010101", lowBound = 0)
x010102 = pl.LpVariable("x010102", lowBound = 0)
x010103 = pl.LpVariable("x010103", lowBound = 0)
x010104 = pl.LpVariable("x010104", lowBound = 0)
x010201 = pl.LpVariable("x010201", lowBound = 0)
x010202 = pl.LpVariable("x010202", lowBound = 0)
x010203 = pl.LpVariable("x010203", lowBound = 0)
x010204 = pl.LpVariable("x010204", lowBound = 0)
x020101 = pl.LpVariable("x020101", lowBound = 0)
x020102 = pl.LpVariable("x020102", lowBound = 0)
x020103 = pl.LpVariable("x020103", lowBound = 0)
x020104 = pl.LpVariable("x020104", lowBound = 0)
x020201 = pl.LpVariable("x020201", lowBound = 0)
x020202 = pl.LpVariable("x020202", lowBound = 0)
x020203 = pl.LpVariable("x020203", lowBound = 0)
x020204 = pl.LpVariable("x020204", lowBound = 0)
# Problem
z = pl.LpProblem("optimizator", pl.LpMinimize)
"OBJECTIVE FUNCTION"
z += ((p1) * (x010101 + x010102 + x010103 + x010104) + (p1) * (x010201 + x010202 + x010203 + x010204) + (p2) * (x020101 + x020102 + x020103 + x020104) + (p2) * (x020201 + x020202 + x020203 + x020204) + (p1) * (x010101 + x010102 + x010103 + x010104) + (p1) * (x010201 + x010202 + x010203 + x010204) + (p2) * (x020101 + x020102 + x020103 + x020104) + (p2) * (x020201 + x020202 + x020203 + x020204))
" CONSTRAINTS "
z += x010101 + x020101 >= 15 * k0101
" SOLUTION "
print(z)
estado = z.solve()
print(pl.LpStatus[estado])
"TOTAL COST:"
print(pl.value(z.objective))
我想简化这个变量的定义,以便能够在更简单的描述中定义更多的变量
现在有谁能将我的变量和参数定义为字典,并在目标函数和约束中考虑?
这将有助于进一步解释这个问题。现在编写的目标函数有重复的术语,很难从概念上理解您试图最小化的内容
也就是说,您可以使用lpSum来表示可变*成本的总和
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