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Diana M.

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  1. Simon Križnik liked a post in a topic by Diana M. in Info about the GRSM algorithm?   
    Hi Rhodel,
    Thank you for your interest in HyperStudy and GRSM.
    I thought you may be interested in looking at this white paper dealing with HyperStudy optimization algorithms benchmark:
    https://www.altair.com/resource/benchmark-of-hyperstudy-optimization-algorithms
     
    Kind regards,
    Diana
  2. Amasker liked a post in a topic by Diana M. in Hyperstudy & Dyna optimization   
    Hi Amasker,
    To smooth the curve in HyperStudy, you can use saefilter or polyfit functions available in the Expression builder. You would need to create data sources for each vector Time and Velocity and then create a Response defined with the filter expression.
     
    Hope it helps. Let us know if further questions.
    Diana
  3. Rahul R liked a post in a topic by Diana M. in Hyperstudy & Dyna optimization   
    Hi Amasker,
    To smooth the curve in HyperStudy, you can use saefilter or polyfit functions available in the Expression builder. You would need to create data sources for each vector Time and Velocity and then create a Response defined with the filter expression.
     
    Hope it helps. Let us know if further questions.
    Diana
  4. Rahul R liked a post in a topic by Diana M. in Create the response from fuction   
    Hello,
    I confirm you that you can create a response of f(x1,x2) as (var_2-(5*var_1^2)/(4*pi^2)+var_1/pi-6)^2+10*(1-1/8*pi)*cos(var_1)+10, where var_1 is x1 and var_2 is x2
    It works: f(1,1)=36.4
    What was not working in your case? 
     
    Best regards
     
     
  5. Sriramaero liked a post in a topic by Diana M. in Design variable decimals   
    Hello, 
     
    In addition of Rahul's answers I would like to provide some additional information. 
    1) Let me come back to your initial request. You said that your optimization with GRSM did not provide a satisfying solution. I would suggest to investigate this. Please, find attached some good practices on GRSM use that may help you to get insight on your optimization.  
    2) Menu File --> Export archive allows packaging the study files in archive file (.hstx).
    3) The values precision for continuous dvs is managed internally by HyperStudy. If you would like that dvs take specific values (with less decimals) you may prefer using discrete variables instead of continuous ones. Thus, you can specify the variation step (ex. 0.1) in the allowed range.
     
    Hope it helps. 
    GRSM_good_practices.pdf
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