returning additional values from a fitness function for genetic optimisation
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Is there a simple way to return additional values from a fitness function (in addition to the objective value) when using an optimisation algorithm, such as genetic algorithm or multi-objective ga in matlab?
For example, it is easy enough to specify additional parameters to be passed to a fitness function using a function handle:
f = @(x)parameterfun(x,a,b,c);
However, is possible to do something similar for the outputs of the fitness function?
Some ideas I had include saving the values in the fitness-function to a file, and then reading them in after the ga has finished in the parent function, or saving the values as global variables, but is there a simpler approach?
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Alan Weiss
2015년 9월 16일
You can use nested functions to do what you want. The example of a nested output function might help.
Alan Weiss
MATLAB mathematical toolbox documentation
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Alan Weiss
2017년 8월 15일
You pass extra variables to an output function in exactly the same way that you pass extra parameters anywhere else.
Alan Weiss
MATLAB mathematical toolbox documentation
A Desai
2017년 8월 15일
Do you mind showing me what that would look like using the above sample code? I understand passing the extra parameters in the example provided in the link, which is similar to passing variables into the fitness function, but i cant seem to get it to work from the ga to the output function. From what I understood so far, I've added the following to the options line:
options = optimoptions('ga','CreationFcn',@gacreationframework,...
'OutputFcn',@(options,state,flag)gaoutputframework(options,state,flag,fout),...
'MaxGenerations',1,...
'PopulationSize',4,...
'UseVectorized',false,...
'UseParallel',true); %
and followed a similar line with the output function:
function [state,options,optchanged] = gaoutputframework(options,state,flag,fout)
where fout contain the extra parameters within the fitness function. But this doesnt work...
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