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One way, not necessarily the best way to do this is to work from
coarse to fine ...
For example lets assume you have 4 variables that could have values
of 0 to 100 which you'd like to simultaneously optimize based on
something to achieve the best results yielding an integer for each
variable. 100^4 of course might be able to be done but you might
have to take a week off to have the answer. But you might also be
able to get at an answer more quickly without overlooking potentially
good results by first running the optimizations as 0 to 100 by 25,
seeing where the best results are and then scaling down the range and
the increment for the next pass i.e. if the first run shows 50 as the
best place to be then on pass 2 you might want to set the values as
10 to 90 by 20 etc. If you are careful how you write the code for
the optimization statements this can be done in one pass from an
AB/AA/AFL perspective.
--- In amibroker@xxxxxxxxxxxxxxx, "Gary A. Serkhoshian"
<serkhoshian777@xxxx> wrote:
> Hi all,
>
> I should preface this e-mail by saying that I'm not trying to
create a Rube Goldberg as I can go through the process ourlined below
manually. So, if what I'm suggesting requires a Rube Goldberg type
solution let me know, and I'll let it go.
>
> Essentially what I'm doing with optimizations over multiple
variables is prioritizing variables on importance, and optimizing one
variable at a time leaving the others static. I just keep iterating
through all the variables until things stabilize in terms of standard
measures. The cocktail party term is genetic algorithms, but between
us it's necesary as optimizing over multiple variables (4+) will
either take too long or worse cause AmiBroker to crash due to memory
issues.
>
> Here's the punchline. Can you all give some input on ways to
program this in afl so as to automate the process outlined above
rather than me manually iterating through as it is labor intensive.
>
> Many thanks,
> Gary
>
>
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