There is a large number of optimization test functions (for 
derivative-free, black-box optimization) implemented in pure Julia in 
Robert Feldt's BlackBoxOptim.jl.   From the source code comments in 
single_objective.jl, functions are taken from the following sources:

*  CEC 2013 competition on large-scale optimization
*  JADE paper http://150.214.190.154/EAMHCO/pdf/JADE.pdf
*  "Test Suite for the Special Issue of Soft Computing on Scalability of 
Evolutionary 
    Algorithms and other Metaheuristics for Large Scale Continuous 
Optimization 
    Problems", http://sci2s.ugr.es/eamhco/functions1-19.pdf  

--Peter


On Sunday, July 27, 2014 9:31:41 AM UTC-7, Tim Holy wrote:
>
> Nope. 
>
> One could write a SIF parser from scratch, but it would take some time. 
>
> --Tim 
>
> On Sunday, July 27, 2014 08:51:51 AM John Myles White wrote: 
> > Is CUTEst.jl easier to get working these days? The issue I opened in 
> March 
> > seems to still be open. 
> > 
> >  — John 
> > 
> > On Jul 27, 2014, at 6:40 AM, Tim Holy <[email protected] <javascript:>> 
> wrote: 
> > > A package of test functions sounds worthwhile. There's also CUTEst.jl: 
> > > https://github.com/lpoo/CUTEst.jl 
> > > 
> > > --Tim 
> > > 
> > > On Sunday, July 27, 2014 06:25:28 AM Hans W Borchers wrote: 
> > >> Ken: 
> > >> 
> > >> (1) Thanks for pointing out this approach and for implementing it. 
> > >> Unfortunately, I was not able to locate your code at Github. I would 
> > >> certainly try it out on some of my examples in global optimization. 
> > >> 
> > >> (2) Did you include (or do you plan to include) the improvements of 
> > >> MinFinder, 
> > >> as discussed in "MinFinder 2.0: An improved version of MinFinder" by 
> > >> Tsoulos and Lagaris? 
> > >> 
> > >> (3) Also this article contains examples of functions with many local 
> > >> minima. Most of these are test functions for global optimization 
> > >> procedures. Did you test your function on these examples? 
> > >> 
> > >> I have implemented  some of these functions for my own purposes. 
> > >> I wonder whether it would be useful to have a Julia package of its 
> own 
> > >> for 
> > >> compiling optimization test functions. 
> > >> 
> > >> (4) Are you sure/Is it guaranteed MinFinder will *reliably* find 
> *all* 
> > >> local minima? 
> > >> This is a difficult problem, and for example there is a long 
> discussion 
> > >> on 
> > >> this topic in Chapter 4, by Stan Wagon, in the book "The SIAM 100 
> Digit 
> > >> Challenge" about all the preventive measures to be taken to be able 
> to 
> > >> guarantee to find all local minima -- and thus also the one global 
> > >> minimum. 
> > >> 
> > >> On Sunday, July 27, 2014 8:26:31 AM UTC+2, Ken B wrote: 
> > >>> Hi Charles, 
> > >>> 
> > >>> You can have a look at the MinFinder algorithm for which I've just 
> > >>> created 
> > >>> a pull request to Optim.jl (talk about a coincidence!): 
> > >>> https://github.com/JuliaOpt/Optim.jl/pull/72 
> > >>> 
> > >>> I'd like to add the possibility to run each optimization in 
> parallel, 
> > >>> but 
> > >>> I have no experience with these things, although I have time to 
> learn 
> > >>> :). 
> > >>> Would you like to collaborate on this? 
> > >>> 
> > >>> Does anyone know of some parallel sample code to have a look at? 
> > >>> Basically 
> > >>> it's sending each optimization problem to a separate worker and 
> getting 
> > >>> the 
> > >>> results, taking into account that some optimizations might take much 
> > >>> longer 
> > >>> than others. 
> > >>> 
> > >>> Cheers, 
> > >>> Ken 
> > >>> 
> > >>> On Saturday, 26 July 2014 23:13:28 UTC-5, Charles Martineau wrote: 
> > >>>> Yes I could do that but it is simpler (I think) to execute the code 
> in 
> > >>>> parallel instead of sending 20 codes to be executed on the cluste.r 
> > >>>> 
> > >>>> On Saturday, July 26, 2014 10:08:20 AM UTC-7, Michael Prentiss 
> wrote: 
> > >>>>> What you are doing makes sense.  Starting from multiple starting 
> > >>>>> points 
> > >>>>> is important. 
> > >>>>> 
> > >>>>> I am curious why you just don't just run 20 different 1-processor 
> jobs 
> > >>>>> instead of bothering with the parallelism? 
> > >>>>> 
> > >>>>> On Saturday, July 26, 2014 11:22:07 AM UTC-5, Iain Dunning wrote: 
> > >>>>>> The idea is to call the optimize function multiple times in 
> parallel, 
> > >>>>>> not to call it once and let it do parallel multistart. 
> > >>>>>> 
> > >>>>>> Check out the "parallel map and loops" section of the parallel 
> > >>>>>> programming chapter in the Julia manual, I think it'll be clearer 
> > >>>>>> there. 
> > >>>>>> 
> > >>>>>> On Friday, July 25, 2014 8:00:40 PM UTC-4, Charles Martineau 
> wrote: 
> > >>>>>>> Thank you for your answer. So I would have to loop over, say 20 
> > >>>>>>> random 
> > >>>>>>> set of starting points, where in my loop I would use the Optim 
> > >>>>>>> package 
> > >>>>>>> to 
> > >>>>>>> minimize my MLE function for each random set. Where online is 
> the 
> > >>>>>>> documents 
> > >>>>>>> that shows how to specify that we want the command 
> > >>>>>>> 
> > >>>>>>> Optim.optimize(my function, etc.) to be parallelized? Sorry for 
> my 
> > >>>>>>> ignorance, I am new to Julia!>>>>> 
> > >>>>>>> 
> > >>>>>>> On Friday, July 25, 2014 2:04:08 PM UTC-7, Iain Dunning wrote: 
> > >>>>>>>> I'm not familiar with that particular package, but the Julia 
> way to 
> > >>>>>>>> do it could be to use the Optim.jl package and create a random 
> set 
> > >>>>>>>> of 
> > >>>>>>>> starting points, and do a parallel-map over that set of 
> starting 
> > >>>>>>>> points. 
> > >>>>>>>> Should work quite well. Trickier (maybe) would be to just give 
> each 
> > >>>>>>>> processor a different random seed and generate starting points 
> on 
> > >>>>>>>> each 
> > >>>>>>>> processor. 
> > >>>>>>>> 
> > >>>>>>>> On Friday, July 25, 2014 3:05:05 PM UTC-4, Charles Martineau 
> wrote: 
> > >>>>>>>>> Dear Julia developers and users, 
> > >>>>>>>>> 
> > >>>>>>>>> I am currently using in Matlab the multisearch algorithm to 
> find 
> > >>>>>>>>> multiple local minima: 
> > >>>>>>>>> http://www.mathworks.com/help/gads/multistart-class.html for 
> a MLE 
> > >>>>>>>>> function. 
> > >>>>>>>>> I use this Multisearch in a parallel setup as well. 
> > >>>>>>>>> 
> > >>>>>>>>> Can I do something similar in Julia using parallel 
> programming? 
> > >>>>>>>>> 
> > >>>>>>>>> Thank you 
> > >>>>>>>>> 
> > >>>>>>>>> Charles 
>
>

Reply via email to