Vectorizing the fitness function of a genetic algorithm
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Dear MATLAB Community,
I am currently trying to solve a binary nonlinear problem through ga, but it just takes too long. I came across the following page (see vectorize for speed): https://www.mathworks.com/help/gads/vectorizing-the-fitness-function.html
I understand the logic, however; I have 6210 dimensions in the decision vector and I was wondering if there was another way to write the function in detail as expressed on that page.
My fitness function currently looks as follows:
A = abs(X-X_Stern);
y = c*A';
where X, X_Stern and c are vectors (1x6210).
Is there a way to vectorize for speed without having to write in open format?
I appreciate your time and answer.
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Carl
2017 年 4 月 4 日
編集済み: Carl
2017 年 4 月 4 日
Hi Atamert, I believe the way you have it structured now should work fine. If pop is the population size, the input to your fitness function will be popx6210. The output of that calculation is a vector of length pop, which is what's required from a vectorized fitness function.
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