创建一个 for 循环以将变量添加到 Gurobi Optimizer 中而没有多余的变量

Question

我正在尝试在 Gurobi 中添加变量。我有以下代码：

from gurobipy import *
rangevalue = list(range(8,13))
E = [6, 3, 4, 2, 4, 2, 5, 1, 4, 2]

y = [(m.addVar(name="y%s" % str([i+1, rangevalue[0] - t])
               .format(i+1, rangevalue[0] - t))) for i,t in enumerate(E)]
m.update()
y  #You can directly run this code and see the following output:

[<gurobi.Var y[1, 2]>,
 <gurobi.Var y[2, 5]>,
 <gurobi.Var y[3, 4]>,
 <gurobi.Var y[4, 6]>,
 <gurobi.Var y[5, 4]>,
 <gurobi.Var y[6, 6]>,
 <gurobi.Var y[7, 3]>,
 <gurobi.Var y[8, 7]>,
 <gurobi.Var y[9, 4]>,
 <gurobi.Var y[10, 6]>]

这就是我想要的。但是，我还想在rangevalue为[1]、[2]、[3]、[4]时添加更多变量.....max in rangevalue.我的rangevalue不限于范围(8,13)，可以更高。那么，基于此，我如何构造一个循环来添加所有 y 变量？

这是我失败的尝试：

for k in range(rangevalue)
    y[k] = [(m.addVar(name="y%s" % str([i+1, rangevalue[k] - t])
                   .format(i+1, rangevalue[k] - t))) for i,t in enumerate(E)]

Answer 1

好吧，我只是在这里找到了自己的答案和分享。也许有人可以受益：

for i in range(I):
    for k in range(len(rangevalue)):
        t = E[i]
        y[i+1, rangevalue[k] - t] = m.addVar(vtype=GRB.BINARY,
           name="y%s" % str([i+1, rangevalue[k] - t]))
m.update()        
y

输出：

{(1, 2): <gurobi.Var y[1, 2]>,
 (1, 3): <gurobi.Var y[1, 3]>,
 (1, 4): <gurobi.Var y[1, 4]>,
 (1, 5): <gurobi.Var y[1, 5]>,
 (1, 6): <gurobi.Var y[1, 6]>,
 (2, 5): <gurobi.Var y[2, 5]>,
 (2, 6): <gurobi.Var y[2, 6]>,
 (2, 7): <gurobi.Var y[2, 7]>,
 (2, 8): <gurobi.Var y[2, 8]>,
 (2, 9): <gurobi.Var y[2, 9]>,
 (3, 4): <gurobi.Var y[3, 4]>,
 (3, 5): <gurobi.Var y[3, 5]>,
 (3, 6): <gurobi.Var y[3, 6]>,
 (3, 7): <gurobi.Var y[3, 7]>,
 (3, 8): <gurobi.Var y[3, 8]>,
 (4, 6): <gurobi.Var y[4, 6]>,
 (4, 7): <gurobi.Var y[4, 7]>,
 (4, 8): <gurobi.Var y[4, 8]>,
 (4, 9): <gurobi.Var y[4, 9]>,
 (4, 10): <gurobi.Var y[4, 10]>,
 (5, 4): <gurobi.Var y[5, 4]>,
 (5, 5): <gurobi.Var y[5, 5]>,
 (5, 6): <gurobi.Var y[5, 6]>,
 (5, 7): <gurobi.Var y[5, 7]>,
 (5, 8): <gurobi.Var y[5, 8]>,
 (6, 6): <gurobi.Var y[6, 6]>,
 (6, 7): <gurobi.Var y[6, 7]>,
 (6, 8): <gurobi.Var y[6, 8]>,
 (6, 9): <gurobi.Var y[6, 9]>,
 (6, 10): <gurobi.Var y[6, 10]>,
 (7, 3): <gurobi.Var y[7, 3]>,
 (7, 4): <gurobi.Var y[7, 4]>,
 (7, 5): <gurobi.Var y[7, 5]>,
 (7, 6): <gurobi.Var y[7, 6]>,
 (7, 7): <gurobi.Var y[7, 7]>,
 (8, 7): <gurobi.Var y[8, 7]>,
 (8, 8): <gurobi.Var y[8, 8]>,
 (8, 9): <gurobi.Var y[8, 9]>,
 (8, 10): <gurobi.Var y[8, 10]>,
 (8, 11): <gurobi.Var y[8, 11]>,
 (9, 4): <gurobi.Var y[9, 4]>,
 (9, 5): <gurobi.Var y[9, 5]>,
 (9, 6): <gurobi.Var y[9, 6]>,
 (9, 7): <gurobi.Var y[9, 7]>,
 (9, 8): <gurobi.Var y[9, 8]>,
 (10, 6): <gurobi.Var y[10, 6]>,
 (10, 7): <gurobi.Var y[10, 7]>,
 (10, 8): <gurobi.Var y[10, 8]>,
 (10, 9): <gurobi.Var y[10, 9]>,
 (10, 10): <gurobi.Var y[10, 10]>}

创建一个 for 循环以将变量添加到 Gurobi Optimizer 中而没有多余的变量

Creating a for loop to add variables into Gurobi Optimizer without redundant ones

python

optimization

gurobi