[SciPy-Dev] Global Optimization Benchmarks

[Daniel Schmitz]

Awesome work, Andrea!

Would it be possible for you to make your implementations of mcs and
biteopt publicly available? And more out of curiosity, not directly related
to scipy: since you work in an industry setting, did you compare these open
source optimizers against commercial ones like knitro?

Cheers,

Daniel

On Fri, 8 Jan 2021 at 12:28, Ralf Gommers <ralf.gommers at gmail.com> wrote:

>
>
> On Fri, Jan 8, 2021 at 12:20 PM Andrea Gavana <andrea.gavana at gmail.com>
> wrote:
>
>> Hi Ralf,
>>
>> On Fri, 8 Jan 2021 at 12:15, Ralf Gommers <ralf.gommers at gmail.com> wrote:
>>
>>>
>>>
>>> On Fri, Jan 8, 2021 at 11:35 AM Andrea Gavana <andrea.gavana at gmail.com>
>>> wrote:
>>>
>>>> Hi Ralf,
>>>>
>>>> On Fri, 8 Jan 2021 at 11:07, Ralf Gommers <ralf.gommers at gmail.com>
>>>> wrote:
>>>>
>>>>>
>>>>>
>>>>> On Fri, Jan 8, 2021 at 10:21 AM Andrea Gavana <andrea.gavana at gmail.com>
>>>>> wrote:
>>>>>
>>>>>> Dear SciPy Developers & Users,
>>>>>>
>>>>>>     long time no see :-) . I thought to start 2021 with a bit of a
>>>>>> bang, to try and forget how bad 2020 has been... So I am happy to present
>>>>>> you with a revamped version of the Global Optimization Benchmarks from my
>>>>>> previous exercise in 2013.
>>>>>>
>>>>>
>>>>> Hi Andrea, this is awesome! Thanks for sharing!
>>>>>
>>>>
>>>> I am happy you like it :-) .
>>>>
>>>>
>>>>
>>>>> This could be really useful to link to and use as a guide for
>>>>> providing recommendations for solvers to use in the scipy.optimize
>>>>> tutorials. It's good to see that SciPy overall is much more competitive
>>>>> than it was in 2013. Overall it seems SHGO is our most accurate solver, and
>>>>> making it faster seems worthwhile. That shouldn't be very difficult, given
>>>>> that it's all pure Python still.
>>>>>
>>>>
>>>> I have to say that, compared to back in 2013, the addition of SHGO and
>>>> DualAnnealing to SciPy has made the global optimization world in SciPy much
>>>> more powerful, pretty much at the top of what can currently be done with
>>>> open source solvers.
>>>>
>>>>
>>>>> MCS isn't open source, but both DIRECT and BiteOpt are MIT-licensed
>>>>> and seem the best candidates to be considered for inclusion in SciPy.
>>>>>
>>>>
>>>> I couldn't find a license restriction for MCS, but maybe I haven't
>>>> looked hard enough... Do you have a link for it? I am just curious.
>>>>
>>>
>>> MCS itself doesn't contain any license information, but it depends on
>>> MINQ which has a link in "All versions of MINQ are licensed" on this page:
>>> https://www.mat.univie.ac.at/~neum/software/minq/. It's only free for
>>> non-commercial use.
>>>
>>
>>
>> Ah, OK, thank you, I didn't think about that. Of course, assuming SciPy
>> had another, different "bound constrained indefinite quadratic programming"
>> module then we could easily swap it :-) .
>>
>
> MCS and MINQ are from the same author, so I'd expect the same restriction
> to apply to MCS though. We could ask for permission to license all that
> under BSD/MIT, sometimes that works - the author seems like the typical
> academic who doesn't understand open source licensing. In the past we've
> had success with explaining; given how much extra exposure/users MCS gets
> if it would be included in SciPy, it may be worth doing if someone is
> motivated to work on integrating MCS into SciPy.
>
> Cheers,
> Ralf
>
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