对于当前的输入，您得到的是None，因为constraints没有在shgo(rosen, bounds, constraints=constraints)中使用。
根据该文件：https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.shgo.html
约束应该是dict或dict序列。
您的constraints是list。
因此，您必须执行constraints=constraints[0]

from scipy.optimize import shgo,  rosen

# Set up the constraints list
constraints = [{'type': 'ineq', 'fun': lambda x, i=i: x[i+1] - x[i] - 0.1} for i in range(2)]

# Define the variable bounds
bounds = [(0, 20)]*3

# Call the shgo function with constraints
result = shgo(rosen, bounds, constraints=constraints[0])

# Print the optimal solution
print("Optimal solution:", result.x)
print("Optimal value:", result.fun)

#output

Optimal solution: [ 0. 20. 20.]
Optimal value: 14480362.0

编辑：

如果我们打印约束，我们将得到：

[{'type': 'ineq', 'fun': <function __main__.<listcomp>.<lambda>(x, i=0)>},
 {'type': 'ineq', 'fun': <function __main__.<listcomp>.<lambda>(x, i=1)>}]

我们也可以这样做：

# Call the shgo function with constraints
result = shgo(rosen, bounds, constraints=constraints[1])

# Print the optimal solution
print("Optimal solution:", result.x)
print("Optimal value:", result.fun)

output:

Optimal solution: [ 1.77749693  3.16168239 10.        ]
Optimal value: 5.279267671341584