BUG: Documentation for scipy.optimize.differential_evolution is incomplete, reference link is broken

[Dominik1123]

Describe your issue.

The different possible choices for scipy.optimize.differential_evolution, parameter strategy, are not explained in the documentation. Currently, it lists 12 different values:

    strategy : str, optional
        The differential evolution strategy to use. Should be one of:
            - 'best1bin'
            - 'best1exp'
            - 'rand1exp'
            - 'randtobest1exp'
            - 'currenttobest1exp'
            - 'best2exp'
            - 'rand2exp'
            - 'randtobest1bin'
            - 'currenttobest1bin'
            - 'best2bin'
            - 'rand2bin'
            - 'rand1bin'
        The default is 'best1bin'.

Only one of them, the default, is explained in the doc string section Notes. There is reference [2] but the provided link is broken. Also reference [1] does not seem to contain details on what the different strategies mean.
Since this is a critical parameter of the function, it would be good if it is documented properly, so that users can make an informed choice.

Reproducing Code Example

This is a docs issue.

Error message

This is a docs issue.

SciPy/NumPy/Python version information

v1.9.3

[andyfaff]

Seems like ref 2 is stale. https://www.osti.gov/servlets/purl/1163659 also explains what the strategies represent. They give references within that article as well.
Can also reference that paper as "Qiang, JI. (2014). A Unified Differential Evolution Algorithm for Global Optimization. Lawrence Berkeley National Laboratory. Retrieved from https://escholarship.org/uc/item/41b84414"

[Femme-js]

@tupui If this doc enhancement seems important, Can I pick this up?

[mdhaber]

@Femme-js a PR would be welcome.

[mkiffer]

I will try to work on this too.

[meaviral17]

Hi. This project is interesting. I will try to work on this too

[mkiffer]

Can you access the changes I have made? I just wasn’t able to format them correctly and haven’t had a chance to fix them :)