GEKKO错误：“在约束和目标内调用函数时，方程没有等式（=）或不等式（>，<）”

Question

我的代码出现以下错误，我完全不知道错误的来源：

@error: Equation Definition
Equation without an equality (=) or inequality (>,<)
true
STOPPING...

我试图确定解决方案“x”，该方案将函数“was_约束”的结果最小化，但需满足“warf_moodys_约束”设置的约束。这些函数返回一个浮点值，当我将初始起始向量“x”分别传递给每个函数时，我不会收到来自这些函数的任何错误。谁能告诉我哪里出了问题

def was_constraint(sol_g, df, orig):
    sol = gekko_to_numpy(sol_g)
    x1 = orig.loc["Denominator","WAS"]*orig.loc["Current","WAS"]
    x2 = (sol*df["All-In Rate"]).sum()/100
    y1 = orig.loc["Denominator","WAS"]+sum(sol)
    return y1/(x1+x2)

def warf_moodys_constraint(sol_g, df, orig):
    sol = gekko_to_numpy(sol_g)
    x1 = orig.loc["Denominator","Moodys WARF"]*orig.loc["Current","Moodys WARF"]
    x2 = sum(np.where(sol > 0, sol*df["Moody's WARF"], 0))
    y1 = orig.loc["Denominator","Moodys WARF"] +sum(np.where(sol > 0, sol, 0))
    return 3000 - (x1+x2)/y1 

def gekko_to_numpy(sol_g):
    res = np.zeros(len(sol_g))
    for i in range(len(sol_g)):
        res[i] = sol_g[i].value.value
    return res

clo_data = pd.read_excel('CLO.xlsx', sheet_name='CLO')
m = GEKKO()
x = [m.Var() for i in range(len(clo_data["Holdings"]))]

for i in range(len(clo_data["Lower Bound"])):
    x[i].lower = 0
    x[i].upper = 1000000

m.Equation(warf_moodys_constraint(x, clo_data, metrics)>=0)
m.Obj(was_constraint(x, clo_data, metrics))
m.options.IMODE = 3 #steady state optimization
m.solve()

Answer 1

你需要用Gekko变量来定义方程。将Gekko变量转换为Numpy数组的方法无法定义表达式，因为Gekko不会回调Python函数

def gekko_to_numpy(sol_g):
    res = np.zeros(len(sol_g))
    for i in range(len(sol_g)):
        res[i] = sol_g[i].value.value
    return res

Gekko在运行文件夹中构建了gk_model0.apm模型，您可以通过m.open_folder()看到它。当您使用m.solve()进行求解时，Gekko将模型编译为字节码，并使用稀疏非线性解算器（如IPOPT或APOPT）进行求解。如果不能使用Gekko变量，那么scipy.opitimize.minimize()函数可能是更好的选择。这是一个tutorial with that optimizer