Re. (3), I’d like to move the optimization problems we use for testing out of 
Optim into a separate package. Having a nice test suite would be a big gain for 
JuliaOpt.

 — John

On Jul 27, 2014, at 6:25 AM, Hans W Borchers <[email protected]> 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
> 

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