resuming and starting from new line in genetic algorithm after specific generations

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I want to resume and start from new line in genetic algorithm after specific generations.
Has anyone know How is impossible??
Any suggestion may help a lot.
Thank you guys.
Hamid on 9 Nov 2014
Dear Geoff - my final goal is to reaching to best solution under all 7 conditions together, these conditions only difference in f-matrix.
What do you recommend?????
I'm so confused and I'm gonna be crazy.

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Answers (1)

Geoff Hayes
Geoff Hayes on 10 Nov 2014
Hamid - I don't think that I can give a valid recommendation because I don't know enough of what you are trying to do. f seems to be a matrix used in the fitness function, but I can't guess as to its impact or that of changing a handful of its values. But if you want to try and re-use the population after 100 iterations with a slight change to the f matrix, then you could change your return from the ga function of
[x,fval]=ga(@(x) penalty2(x,available,bc,Dof,E...),Nvars,options);
[x,fval,exitflag,output,population] = ga(@(x)penalty2(x,available,bc,Dof, E...),Nvars,options);
The population output parameter will be the final population for (say) 100 iterations of the algorithm. You then update the f matrix, and re-call
% re-use the population as the initial population for the next 100 generations
options = gaoptimset('InitialPopulation', population);
% run the algorithm
[x,fval,exitflag,output,population] = ga(@(x)penalty2(x,available,bc,Dof, E...),Nvars,options);
for 100 more generations. Then change f to whatever you want. You can put this in a loop that iterates from 1 through to 7, and you would change f on each iteration.
However, this method may not work as expected especially if the GA has converged to a premature solution before generation 100. If all members of the population are identical (or near-identical) then there will not be enough genetic diversity in the next round of 100 generations to produce any new members even though you have changed the f matrix.

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