如何在 scipy.optimize.basinhopping 中禁用局部最小化进程？

Question

我正在使用 scipy.optimize.basinhopping 来寻找标量函数的最小值。我想知道是否可以禁用 scipy.optimize.basinhopping 的局部最小化部分？从下面的输出信息可以看出，minimization_failures 和 nit 几乎相同，说明局部最小化部分对于 basinhopping 的全局优化过程可能是无用的——我想的原因为了提高效率，禁用局部最小化部分。

Answer 1

您可以使用 minimizer_kwargs 指定 minimize() 您更喜欢局部最小化步骤的选项。请参阅 docs.

的专用部分

然后取决于您要求 minimize 求解器的类型。您可以尝试设置更大的 tol 以使局部最小化步骤提前终止。

编辑，回复评论"What if I want to disable the local minimization part completely?"

文档中的 basinhopping 算法的工作原理如下：

The algorithm is iterative with each cycle composed of the following features

random perturbation of the coordinates

local minimization accept or

reject the new coordinates based on the minimized function value

如果以上是准确的，则无法完全跳过局部最小化步骤，因为算法需要其输出才能继续进行，即保留或丢弃新坐标。但是，我不是这个算法的专家。

Answer 2

您可以通过使用不执行任何操作的自定义最小化器来避免运行最小化器。

参见 "Custom minimizers" in the documentation of minimize() 上的讨论：

 **Custom minimizers**
It may be useful to pass a custom minimization method, for example
when using a frontend to this method such as `scipy.optimize.basinhopping`
or a different library. You can simply pass a callable as the ``method``
parameter.
The callable is called as ``method(fun, x0, args, **kwargs, **options)``
where ``kwargs`` corresponds to any other parameters passed to `minimize`
(such as `callback`, `hess`, etc.), except the `options` dict, which has
its contents also passed as `method` parameters pair by pair. Also, if
`jac` has been passed as a bool type, `jac` and `fun` are mangled so that
`fun` returns just the function values and `jac` is converted to a function
returning the Jacobian. The method shall return an ``OptimizeResult``
object.
The provided `method` callable must be able to accept (and possibly ignore)
arbitrary parameters; the set of parameters accepted by `minimize` may
expand in future versions and then these parameters will be passed to
the method. You can find an example in the scipy.optimize tutorial.

基本上，您需要编写一个 returns 和 OptimizeResult 的自定义函数，并通过 minimizer_kwargs 的 method 部分将其传递给 basinhopping，例如

from scipy.optimize import OptimizeResult
def noop_min(fun, x0, args, **options):
    return OptimizeResult(x=x0, fun=fun(x0), success=True, nfev=1)

...

sol = basinhopping(..., minimizer_kwargs=dict(method=noop_min))

注意：我不知道跳过局部最小化如何影响 basinhopping 算法的收敛特性。

如何在 scipy.optimize.basinhopping 中禁用局部最小化进程？

How to disable the local minimization process in scipy.optimize.basinhopping?

python

scipy