Google 或来自 DataFrame 的工具约束

Question

我想构建一个 Google OR 工具模型以将 linear_solver 用于 CBC_MIXED_INTEGER_PROGRAMMING。在 Google tutorial 之后，我学会了构建约束，但我有一个问题...是否有必要手写每个约束？我的意思是，我有以下 DataFrame df_constraint，其中包含 ax+by<=c.

形式的约束系数

+---+---+---+
| A | B | C |
+---+---+---+
| 1 | 5 | 7 |
| 2 | 9 | 3 |
| 3 | 0 | 4 |
+---+---+---+

table可以转化为以下约束

# 1x+5y<=7
constraint1 = solver.Constraint(-solver.infinity(), 7)
constraint1.SetCoefficient(x, 1)
constraint1.SetCoefficient(y, 5)

# 2x+9y<=3
constraint2 = solver.Constraint(-solver.infinity(), 3)
constraint2.SetCoefficient(x, 2)
constraint2.SetCoefficient(y, 9)

# 3x<=4
constraint3 = solver.Constraint(-solver.infinity(), 4)
constraint3.SetCoefficient(x, 3)

我想要这样的东西而不是写每一行：

for index, row in df.iterrows():
    constraint = solver.Constraint(-solver.infinity(), row['C'])
    constraint.SetCoefficient(x, row['A'])
    constraint.SetCoefficient(y, row['B'])

我的代码片段不起作用，因为每个约束都必须有不同的名称（例如 constraint1、constraint2、...）。

Answer 1

这样可以解决您的问题吗？

 df_constraints = pd.DataFrame({
    'A': pd.Series([1, 2, 3]),
    'B': pd.Series([5, 9, 0]),
    'C': pd.Series([7, 3, 4]),
    })
for row in df_constraints.itertuples():
    #print("row {}".format(row))
    #print("A {}".format(row[0]))
    #print("B {}".format(row[1]))
    #print("C {}".format(row[2]))
    constraint = solver.Constraint(-solver.infinity(), row[2])
    constraint.SetCoefficient(x, row[0])
    constraint.SetCoefficient(y, row[1])

Answer 2

事实上，OR-Tools 并不要求每个约束都具有唯一的名称。但无论如何，以下内容都给了他们独特的名字。如上所述，如果需要存储约束条件，可以按如下方式在数组中进行。这里我使用了更常见的符号（A 是约束系数，B 是约束 right-hand 边，c 是 objective 系数）。但它会适应您的 Pandas 设置。

from ortools.linear_solver import pywraplp # adapted from one of the examples

inf = float("inf")

AB = [
    [1, 0, 1], # x <= 1
    [0, 1, 2], # y <= 2
    [1, 1, 2], # x + y <= 2
    [-1, -1, 0] # x + y >= 0
]
c = [3, 1]

def main():
    solver = pywraplp.Solver('simple_lp_program',
                             pywraplp.Solver.GLOP_LINEAR_PROGRAMMING)
    x = solver.NumVar(-inf, inf, 'x') # no UB or LB on x, y
    y = solver.NumVar(-inf, inf, 'y')

    cts = []
    for i, (*a, b) in enumerate(AB):
        ct = solver.Constraint(-inf, b, 'ct' + str(i))
        ct.SetCoefficient(x, a[0])
        ct.SetCoefficient(y, a[1])
        cts.append(ct)

    print('Number of constraints =', solver.NumConstraints())
    objective = solver.Objective()
    objective.SetCoefficient(x, c[0])
    objective.SetCoefficient(y, c[1])
    objective.SetMaximization()
    solver.Solve()
    print('Solution:')
    print('Objective value =', objective.Value())
    print('x =', x.solution_value())
    print('y =', y.solution_value())

if __name__ == '__main__':
    main()

Google 或来自 DataFrame 的工具约束

Google OR Tools constraints from DataFrame

python

python-3.x

pandas

constraints

or-tools