Choosing optimal values from the genetic algorithm
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Commented: Vivek on 3 Feb 2023
As GA are probabilistic and indetriministic everytime I run the code I am getting different optimas with the same value of objective function.
How to choose the proper and best optima when the function value remains same for different optimias.
Is there any way to choose the best optima.
Thank you in Advance!!
Sam Chak on 3 Feb 2023
Edited: Sam Chak on 3 Feb 2023
You can try setting the rng to 'default' for the reproducibility of the result.
If the function has multiple extrema, I'd probably set the lower and upper bounds on the design variables, so that the solution is searched and found in the range of interest.
xx = linspace(-pi, pi, 51);
yy = linspace(-pi, pi, 51);
[X, Y] = meshgrid(xx, yy);
Z = (sin(X)).^2 + (cos(Y)).^2;
% contour(X, Y, Z)
surfc(X, Y, Z)
xlabel('x_1'), ylabel('x_2'), zlabel('f(x_1, x_2)')
rng default % For reproducibility
fun = @(x) (sin(x(1))).^2 + (cos(x(2))).^2;
lb = [-pi -pi]; % lower bound
ub = [pi pi]; % upper bound
x = ga(fun, 2, , , , , lb, ub)
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