[SciPy-Dev] feedback on adding global optimiser methods to `minimize`

[Andrew Nelson]

I'd like to gauge the support for adding the global minimizers
(dual_annealing, shgo, differential_evolution, basinhopping) as new
`minimize` methods.

The problems the the 'local' and 'global' optimizers are trying to solve
are very similar and both are specified in the same way, so my thought is
that it would be nice to access them via the same unified interface that
`minimize` offers (but not deprecating the `shgo` function, etc).

It's important that the users are able to understand the distinction
between local and global optimisation and how they go about finding a
minimum. I'm hoping that this could be made plain in the documentation.

The change would allow the following:

```
# global minimizer
minimize(func, x0, bounds=bounds, method='differential-evolution',
constraints=constraints)
# local minimizers
minimize(func, x0,  bounds=bounds, method='SLSQP', constraints=constraints)
minimize(func, x0, bounds=bounds, method='trust-constr',
constraints=constraints)
minimize(func, x0, bounds=bounds, method='L-BFGS-B')
```

Please chip in with what your thoughts are, is it a bad idea, good idea,
etc.

-- 
_____________________________________
Dr. Andrew Nelson


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