指数函数的SCIP优化

Question

我对指数方程求和时遇到问题这就是目标函数。

我还试着把指数方程写成我认为约束可能是解决这个问题的另一种方法问题，但这对我来说也不起作用。

如有任何帮助，我们将不胜感激。

import pandas as pd
from pyscipopt import Model, quicksum, multidict, exp
num_fac_to_open = 1
order_to_open = []
opened_fac = []
closed_fac = [0, 1, 2]
S = [0, 1, 2]
R = [10, 11, 12]
distance_dict = {(0, 10): 300.8, (1, 10): 150.6, (2, 10): 1567.8, (0, 11): 1241.0, (1, 11): 2012.1, (2, 11): 789.2, (0, 12): 563.2, (1, 12): 1798.3, (2, 12): 946.3}
population_dict = {10:54, 11:46, 12:22}
# n is the desired number of facilities to open
n = len(opened_fac) + num_fac_to_open
# create a model
model = Model()
z, y= {}, {}
for s in S:
# x_i is binary, 1 if service facility i is opened, 0 otherwise
z[s] = model.addVar(vtype="B")
for r in R:
# y_i,j is binary, 1 if service facility i is assigned to residential area j, 0 otherwise
y[s, r] = model.addVar(vtype="B")
for r in R:
want_list = (distance_dict[s, r]*y[s, r] for s in S)
want_list_quicksum = quicksum(want_list)
exp_power = population_dict[r]*want_list_quicksum
w = exp(exp_power)
model.setObjective(quicksum([w]), 'minimize')
model.optimize()

此代码中出现的错误为：

Traceback (most recent call last):
File "stack_overflow_code.py", line 38, in <module>
model.setObjective(quicksum([w]), 'minimize')
File "src/pyscipopt/scip.pyx", line 1246, in pyscipopt.scip.Model.setObjective
AssertionError: given coefficients are neither Expr or number but SumExpr

据我所知，目标函数的格式应该是(这是我打印exp_power得到的结果(：

Expr({Term(): 0.0, Term(x4): 12390.400000000001, Term(x8): 39562.6, Term(x12): 20818.6})

然而，一旦添加了指数项(w(，格式就变为：

exp(sum(0.0,prod(12390.400000000001,x4),prod(39562.6,x8),prod(20818.6,x12)))

此外，当添加quicksum[w]时，格式变为：

sum(0.0,exp(sum(0.0,prod(12390.400000000001,x4),prod(39562.6,x8),prod(20818.6,x12))))

目的是最大限度地减少｛r＝1｝^N W_r

其中\W_r=exp(population_dict[r]*sum_{s∈s}d_r，s*y_r，s(∀r∈r

Answer 1

quicksum接受可迭代项，但distance_dict[s, r]*y[s, r] for s in S并没有像您预期的那样返回可迭代项。

尝试将该行简化为多行，并确保在将其输入quicksum之前有一个列表可供使用。

为了在Python中使用列表理解，我们必须将语句括在方括号中。[distance_dict[s, r]*y[s, r] for s in S]。