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How can I store the value at each iteration of a genetic algorithm?

Asked by Sylvain Cornelus on 2 Apr 2019
Latest activity Answered by UNAL
on 13 Sep 2019 at 22:27
I have a simple function and two constraints for my genetic algorithm code
ObjFcn = @myFitness;
nvars = 2; %number of variables
LB = [0 0]; %lower bound
UB = [1 13]; %upper bound
ConsFcn = @myConstraints;
[x,fval] = ga(ObjFcn,nvars,[],[],[],[],LB,UB,ConsFcn,opts);
function y = myFitness(x)
y = 100*(x(1)^2-x(2))^2 + (1-x(1))^2;
end
function [c,c_eq] = myConstraints(x)
c = [x(1)*x(2) + x(1) - x(2) + 1.5; 10 - x(1)*x(2)];
c_eq = [];
end
I would like to store the values of x at each function evaluation, as well as keep track of the generation. I've found a similar question here but I don't really understand what the solution meant as it wasn't very clear. I believe I need to tell my fitness function to store values of the GA function so when the GA function reads the fitness function the input parameters at that iteration are saved... but I would like help on how the syntax would work for such a thing. Any help is appreciated!
I've also looked at the GA options and was unable to find help with my specific issue.

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2 Answers

Answer by Stephan
on 2 Apr 2019
 Accepted Answer

Hi,
you coultd try this way:
[x,fval,vals] = solve_problem
function [x,fval,vals] = solve_problem
ObjFcn = @myFitness;
nvars = 2; %number of variables
LB = [0 0]; %lower bound
UB = [1 13]; %upper bound
ConsFcn = @myConstraints;
iter = 1;
vals = [];
[x,fval] = ga(ObjFcn,nvars,[],[],[],[],LB,UB,ConsFcn);
function y = myFitness(x)
y = 100*(x(1)^2-x(2))^2 + (1-x(1))^2;
vals(iter,1:2) = x;
iter = iter+1;
end
function [c,c_eq] = myConstraints(x)
c = [x(1)*x(2) + x(1) - x(2) + 1.5; 10 - x(1)*x(2)];
c_eq = [];
end
end
After running this you can plot how x(1) and x(2) change over the iterations:
yyaxis left
plot(vals(:,1))
yyaxis right
plot(vals(:,2))
x-vals.PNG
Best regards
Stephan

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Thank you Stephan! Exactly what I was looking for. I'll read up on the ga function to figure out how to store the generation.

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Answer by UNAL
on 13 Sep 2019 at 22:27

You can also extract the data directly from the graph that is obtained by configuring the options:
options = optimoptions('ga','PlotFcn', @gaplotbestf);
After obtaining the graph you can extract ist data:
fig = gcf;
dataObjs = findobj(fig,'-property','YData');
y1 = dataObjs(1).YData;
x1 = dataObjs(1).XData;
figure(7)
plot(x1,y1,'*r')

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