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赵亚军1-Visitor
1-Visitor
Feb 20, 2012 7:35 AM UTC
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can anybody achieve genetic algorithms by programming in mathcad

when i do some multi-objective parameter optimization cases in mathcad,i find that there are only three algorithms that can be used，L-M，Conjugate gradient method and Quasi-Newton method. these methods may can't find the global optimum,or take very long time.nowadays,there are many other algorithms,such as GA(Genetic Algorithm),it may solve these problems easily.

but my mathematics is poor，can any body do it,or has anybody done that?

i want to have a try,but my methematics is poor,at the same time,i am not proficient in programming.

wish for your help.

ValeryOchkovAnswer
24-Ruby IV
Feb 21, 2012 5:24 AM UTC

See the atach

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13 replies

ValeryOchkov24-Ruby IV
24-Ruby IV
Feb 20, 2012 9:29 AM UTC

See please - http://communities.ptc.com/docs/DOC-2565

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    赵亚军1-VisitorAuthor
    1-Visitor
    Feb 21, 2012 12:33 AM UTC

    wow,you are so intelligent

    but your function don't apply to my case.i have more than 2 parameters,can you afford me your worksheet about GA program，my version is Mathcad 15.

    if you can develop a model that can be used to solve all the multi-objective parameter optimization cases,that's more better.such as Minerr,minimize,a generic model，not limited to two parameters.

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    ValeryOchkov24-Ruby IVAnswer
    24-Ruby IV
    Feb 21, 2012 5:24 AM UTC

    See the atach

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      RichardJ19-Tanzanite
      19-Tanzanite
      Feb 20, 2012 3:38 PM UTC

      these methods may can't find the global optimum

      There is no algorithm that can be guaranteed to find the global optimum of a non-linear optimization problem.

      nowadays,there are many other algorithms,such as GA(Genetic Algorithm),it may solve these problems easily.

      Maybe. Maybe not. It depends on the problem: http://en.wikipedia.org/wiki/No_free_lunch_in_search_and_optimization

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      赵亚军1-VisitorAuthor
      1-Visitor
      Feb 21, 2012 1:52 AM UTC


      Richard Jackson 编写:

      There is no algorithm that can be guaranteed to find the global optimum of a non-linear optimization problem.

      as what you said,but i want to have a try,my task got stuck,the most important reason is that it takes so long time，i have tried minimize and minerr,they all failed. if this problem can't be solved,i will get in big trouble. do you have any idea to sovle the problem that the time required to find the minimum is so long?

      this is only a small part of data,if i add more data,it may can't finish the caculation.what i am most concerned about is it can give a result,no matter the local optimum or the global optimum.

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