SAS Optimization, and SAS Simulation Studio

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03-02-2012 11:13 AM

I am optimizing using Proc IML, but I think my optimization would be faster in Proc OPTMODEL. It is a concern because the data set I am using is quite large, much larger than the files I have attached.

I have attached data sets and code for the optimization I run in Proc IML. I would like to be able to do the same optimization in Proc OPTMODEL, but I can’t find much help from examples or from the documentation. If you could point me in the right direction, I would appreciate it.

My data set is made up of stocks and dates. In Proc Optmodel, I would like to sum over all stocks each date, and then finally sum over all dates. The number of stocks can change from date to date.

I have attached a paper that describes the methodology. I am estimating theta in equation 6 of the paper.

Any ideas on how to get started would be great!

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Solution

03-06-2012
10:02 AM

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03-06-2012 10:02 AM

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03-05-2012 04:09 PM

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03-05-2012 04:18 PM

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03-06-2012 09:11 AM

One reason that your IML code is slow is that you are re-reading the wgtfracsas and equalsas data sets at every iteration of the optimization, even though those values are unchanged during the optimization.

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03-06-2012 09:49 AM

I noticed that when I wrote the code, but I couldn't figure out a way to get around it. Any suggestions? I feel more comfortable working in IML than I do in OPTMODEL, but speed is of the essence.

Rick Wicklin wrote:

Solution

03-06-2012
10:02 AM

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03-06-2012 10:02 AM

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03-07-2012 12:39 PM

Thank you for the suggestions. The slow (old) and fast (new) versions of the code are attached.

Rick Wicklin wrote:

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03-07-2012 03:03 PM

I ran both the IML code and the OPTMODEL code on the larger data set.

In one run, the IML code returned an objective function equal to -0.218421215, compared to the OPTMODEL objective function of -0.218421214. The IML procedure took 4.13 seconds in real time and 3.99 seconds in cpu time, compared to OPTMODEL, which took 48.82 seconds of real time and 48.43 seconds of cpu time.

In another run, the IML code returned an objective function equal to -0.218605342, compared to the OPTMODEL objective function of -0.218605307. The IML procedure took 3.77 seconds in real time and 3.77 seconds in cpu time, compared to OPTMODEL, which took 51.44 seconds of real time and 51.43 seconds of cpu time.

So, the gains from using OPTMODEL appear small in terms of getting a better objective function, and there is a big loss in time. I will have to find out why I was told that there were such large gains to using OPTMODEL.

The output files and log files are attached in pdf format.

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03-07-2012 03:23 PM

You should see some performance gains from using IMPVAR (available starting in 9.22) and the new NLP solvers (available in 9.3).

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03-07-2012 03:30 PM

Even in 9.2, you might try moving the declarations of DATES and STOCKS until after the READ DATA statement.

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03-07-2012 03:59 PM

Thank you for your suggestions. I didn't get any gains from moving the statements around. I guess I will have to wait for the new version of SAS. I have attached the code and here is a link to the large data set, if you are still curious about the gains from moving to 9.3.

https://bearspace.baylor.edu/xythoswfs/webui/_xy-7387784_1-t_uQw6Wj58

RobPratt wrote:

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03-08-2012 04:37 PM

Thanks for providing the larger data set. I found that your OPTMODEL code runs roughly 8 times as fast in 9.3 as compared to 9.2. Although the NLP solvers have improved significantly in 9.3, this problem has only 3 variables, and you will typically not see much gain from the solvers when there is a small number of variables and constraints. Instead, the 8-fold speedup here is due to OPTMODEL problem generation improvements.

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03-08-2012 06:16 PM

That is great to hear! I hope I can get 9.3 soon then. I'll have to see what the holdup on getting it for us is.

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03-07-2012 05:40 PM

Just for reference, how much improvemnt was there from the "slow version" to the "fast" version of the IML program? The slow version took ____ seconds; the fast one takes 4 seconds.

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03-07-2012 06:01 PM

The slow version took 20 seconds. I have attached code, output, a log file, and the extra data set needed. As above, the other large data set can be found here: https://bearspace.baylor.edu/xythoswfs/webui/_xy-7387784_1-t_uQw6Wj58 .

If I run a simulation, I could be doing this 20,000 or even 100,000 times. So, this makes a big difference.

Rick Wicklin wrote: