when using genetic algorithm, the number of variables(nvar) is dependant on the row vector(x) that my fitness function accepts. How can I deal with that?
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Hello all,
I need to write something like this: ga(h, sum(x(1:5)),[],[],[],[],LB,UB,[],[],ga_opts);
as you see, the number of variables (nvar) is dependant on the vector I want to optimize(x). Is there any way I can deal with this problem?
Thank you
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Answers (2)
amanita
on 29 Nov 2013
I dont know if this is relevant, but i usually set nvars as the maximum number of variables and keep in the fitness function only the ones needed. For example, i have a vector of coefficients W that i want to optimize, but its length is dependent on an integer variable I, ie; If i have I=2 i need a vector W with 2 elements, if I=4 i need W with 4 elements. If the maximum number for I is 10. Then:
h = @(X) NETWORK_mex(X);
nvars=11;
LB=[1 -1*ones(1,10)]
UB=[10 ones(1,10)]
[x, err] = ga(h, nvars,[],[],[],[],LB,UB,[],1,ga_opts);
And inside the fitness function:
function J=NETWORK(X)
I=X(1);
W=X(2:I+1);
...
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