Genetic Algorithms (Error is too big)
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Greetings , i'm doing a parametric optimization for the induction machine ,i've made a simulink model and a mathematical model for the implentation on the GA toolbox, the function works fine when i excute the optimization from the toolbox , but the results are just awfull (never gone under 300) , knowing that i'm minimazing the function , a such results is way out of the acceptable , any thoughts on how to get better results ? , cuz i've been fiddling with it since a relatively long time and it doesn't seem to work
if you need to see the programmes , just comment here and leave your email or something and i'll send them to you , plz i really need help with this for my project
7 Commenti
Walter Roberson
il 12 Ago 2012
Note: several of the volunteers cannot handle .rar files. (On the other hand the ones I know of also do not have Simulink or the GA toolbox)
Lotfi
il 13 Ago 2012
Walter Roberson
il 13 Ago 2012
Modificato: Walter Roberson
il 13 Ago 2012
No they are not.
>> version
ans =
7.14.0.739 (R2012a)
>> simulink
Undefined function or variable 'simulink'.
>> ga
Undefined function or variable 'ga'.
Are you perhaps thinking of the Student Version?
Walter Roberson
il 14 Ago 2012
I have R2012a, the full-priced commercial version purchased only a few weeks ago, and it does NOT include Simulink or the Optimization Toolbox, or any of the other MATLAB toolboxes. The particular PC you used might have happened to have those installed.
Some of the volunteers do have Simulink and also the Global Optimization toolbox. I would have difficulty in remembering exactly whom, though. I do not recall any of the 50 most active volunteers as happening to having experience with both, but I don't read everything here (just most things.)
Historically, most questions about GA go unanswered. That's just the way it goes with volunteers: sometimes people just do not have the resources or experience or the interest to answer.
Risposte (1)
Alan Weiss
il 14 Ago 2012
If you have GA, then you also have PATTERNSEARCH. I recommend PATTERNSEARCH as a more reliable, faster algorithm.
The only difficulty using PATTERNSEARCH is generating initial points. If you have bounds for all variables, you can use
x0 = lb + rand(size(lb)).*(ub - lb);
You can also experiment with tuning PATTERNSEARCH more easily than tuning GA. For example, try different poll methods.
Alan Weiss
MATLAB mathematical toolbox documentation
1 Commento
Lotfi
il 15 Ago 2012
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