谁能检查一下这段代码,告诉我为什么for循环会变得无限?我需要一双全新的眼睛。谢谢!
var routeData = [{"id":1,"c1_id":43,"c2_id":56,"cost":20,"c1_x":658,"c1_y":68,"c2_x":568,"c2_y":149,"owned":false},{"id":2,"c1_id":27,"c2_id":56,"cost":2
我是Python中CP问题和OR-Tools方面的新手,我想做以下工作:
# declare variables
for i in range(I):
for k in range(K):
x[i,k]=solver.IntVar(0,N,"x %i %i " % (i,k))
#constraints
solver.Add(CustomFunction[(x[i,k])] == 1) # only consider the values of x[i,k] evaluated in CustomFunction is equal to 1
但是,在评
我试图写一个正确的线性上下文无关文法,其中0和1的数之间的差应该是偶数。例如:
010001 = 4 - 2 = 2 (even)
我有一个。也许能帮上忙!我想把它写在prolog上。我做了另外10项练习,但这对我来说太难了。对怎么做有什么想法吗?
我的代码
s --> [].
s --> [1],a.
s --> [0],b.
a --> [1],s.
a --> [0],c.
b --> [1],c.
b --> [0],s.
c --> [].
c --> [1],b.
c --> [0],a.
这在很多情况下都是可行的,
使用文本格式的Z3,我可以使用define-fun来定义函数,以便稍后重用。例如:
(define-fun test((a Int) (b Int)) Int
(ite (and (> a 2) (<= b 3))
1
(ite (and (<= a 2)(> b 10))
2
a
)
)
)
所以我想知道如何定义使用C#应用程序接口的乐趣,因为Context.MkFuncDecl仅用于生
import numpy as np
from scipy.optimize import linprog
b_ub = [74, 40, 36]
b_eq = [20, 45, 30]
A = np.array([[7, 3, 6], [4, 8, 2], [1, 5, 9]])
m, n = A.shape
c = list(np.reshape(A, n * m)) # Convert matrix A to list c.
A_ub = np.zeros([m, m * n])
for i in np.arange(0, m,
1): # F
我对优化代码有一个问题。我写的代码应该优化这两个目标,考虑它们的表达式,并产生可以绘制的值。这是我的代码,如下所述。 from pyomo.environ import *
import numpy as np
import pandas as pd
import random
import matplotlib.pyplot as plt
model = ConcreteModel()
st1 = []
st2 = []
rows =10
n = []
for i in range(rows):
rn = random.randi