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
2015-9-16
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
2017-8-15
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
2017-8-15
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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