Python GEKKO使用if语句在模型中使用函数

Question

我正试图用GEKKO Python解决一个非线性优化问题。我知道我可以将自己的函数传递给中间函数或目标函数，但由于中间函数是分段函数，所以我需要if语句。

例如：

这是我测试的结果

def calc_weighted_average(values, characteristic):
# values are the model's variables that are changed by GEKKO.
# characteristic are always the same (they are a constant list I've defined).
sum = 0
for i in range(values):
sum += values[i] * characteristic[i]
return sum / m.sum(values)
weighted_average_density = m.Intermediate(calc_weighted_average(values, density_list))

这不起作用，我不知道如何让它发挥作用

def calc_weighted_average(values, characteristic):
# values are the model's variables that are changed by GEKKO.
# characteristic are always the same (they are a constant list I've defined).
sum = 0
for i in range(values):
sum += values[i] * characteristic[i]
# Correction factor when too large
if sum > 5:
correction_factor = (sum - 5) * (0.984 ** 2)
else:
correction_factor = 0
return (sum / m.sum(values)) - correction_factor
weighted_average_density = m.Intermediate(calc_weighted_average(values, density_list))

Answer 1

尝试m.if3()函数。代替：

if sum > 5:
correction_factor = (sum - 5) * (0.984 ** 2)
else:
correction_factor = 0

尝试以下代码：

correction_factor = m.if3(sum-5,0,(sum-5)*(0.984**2))

m.if2()函数也可用作具有互补约束的数学程序(MPCC(的逻辑条件。m.if3()函数使用二进制变量，通常性能更好，但对于大规模问题，使用许多二进制变量可能会减慢速度。