盖科:盖科不接受MINLP选项

Question

我正在尝试使用gekko解决MINLP问题。我的代码如下：

m = GEKKO(remote = False)
m.options.SOLVER = 3
m.solver_options = ['minlp_maximum_iterations 500', 
# minlp iterations with integer solution
'minlp_max_iter_with_int_sol 10', 
# treat minlp as nlp
'minlp_as_nlp 0', 
# nlp sub-problem max iterations
'nlp_maximum_iterations 50', 
# 1 = depth first, 2 = breadth first
'minlp_branch_method 1', 
# maximum deviation from whole number
'minlp_integer_tol 0.05', 
# covergence tolerance
'minlp_gap_tol 0.01']
rows  = nb_phases + 3*b_max*(nb_phases+1)
x = np.empty(rows,dtype=object)
for i in range(3*nb_phases*b_max+nb_phases+1):
x[i] = m.Var(value = xinit[i], lb = LB[i], ub = UB[i], integer = False)
for i in range(3*nb_phases*b_max+nb_phases+1, (3*nb_phases+3)*b_max+nb_phases):
x[i] = m.Var(value = xinit[i], lb = LB[i], ub = UB[i], integer = True)
# Constraints
m.axb(A,B,x,etype = '<=',sparse=False) 
m.axb(A_eq,B_eq,x,etype = '=',sparse=False)
# Objective Function
f = objective_fun(x, t, ob, jofbuses, q, qc, s, oa, k, l, T, G_next, C, Y, G_previous)
m.Obj(f)
#Solver
m.solve(disp = False)

我得到以下异常：

异常消息：读取选项："；minlp_maximum_iterations"；。这不是一个有效的选项。检查可用选项列表。

对于所有其他选项，我都有同样的例外。

我尝试将解算器更改为m.options.solver=1，但随后出现错误：

错误：异常：Acess冲突Traceback：不可用，使用-ftrace=frame或-ftrace=full编译错误：找不到"results.json"。

我在上面的代码中调用的objective_fun函数如下：

def objective_fun(x, t, ob, jofbuses, q, qc, s, oa, k, l, T, G_next, C, Y, G_previous):
nb_phases = len(G_next)
b_max = len(t)
no_lanegroups = len(q)
obj = 0
G = x[0:nb_phases]

for j in range(no_lanegroups):
delay_a = 0.5*q[j]/(1-q[j]/s[j]) * (pow((sum(G_previous[l[j]:nb_phases]) + sum(G[0:k[j]-1]) + sum(Y[l[j]-1:nb_phases]) + sum(Y[0:k[j]-1])),2) + pow(sum(G[l[j]:nb_phases]) + sum(G_next[0:k[j]-1]) + sum(Y[l[j]-1:nb_phases]) + sum(Y[0:k[j]-1]),2))   

obj = obj + oa*delay_a
for b in range(b_max): 
delay_b1 = x[(3*nb_phases+1)*b_max + nb_phases + b]*(q[jofbuses[b]-1]/s[jofbuses[b]-1] * (t[b] - (T-1)*C + sum(G_previous[l[jofbuses[b]-1]:nb_phases]) + sum(Y[l[jofbuses[b]-1] -1:nb_phases])) + (T-1)*C - t[b] + sum(Y[0:k[jofbuses[b]-1]-1])) 
delay_b2 = x[(3*nb_phases+2)*b_max + nb_phases + b-1]*(q[jofbuses[b]-1]/s[jofbuses[b]-1] * (t[b] - (T-1)*C - sum(Y[0:l[jofbuses[b]-1]-1])) + T*C + sum(G_next[0:k[jofbuses[b]-1]-1]) + sum(Y[0:k[jofbuses[b]-1]-1]) - t[b]) 
delay_b3 = sum(x[nb_phases*b_max + nb_phases*b:nb_phases*b_max + nb_phases*b+k[jofbuses[b]-1]-1]) - q[jofbuses[b]-1]/s[jofbuses[b]-1]*sum(x[2*nb_phases*b_max + nb_phases*b:2*nb_phases*b_max + nb_phases*b +l[jofbuses[b]-1]])
delay_b = delay_b1+delay_b2 +delay_b3 
obj = obj + delay_b*ob[b]       

return obj

此外，如果我不指定选项，我可以运行代码并找到一个成功的解决方案。然而，x数组的一些元素应该是整数，但我得到的解决方案不考虑这个条件。

你能帮我想办法解决这些问题吗？非常感谢！

Answer 1

选项minlp_maximum_iterations不是IPOPT解算器的可用选项之一。您正确地发现，切换到m.options.SOLVER=1(APOPT解算器(可以解决此错误。

解算器未找到解决方案。我推荐一种初始化策略，首先用IPOPT解决，没有选项。接下来，使用APOPT选项再次求解，看看IPOPT非整数解决方案是否有助于作为寻找最佳整数解决方案的起点。