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Highlights from
Genetic Algorithm to Optimise Schaffer's F6 Function

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from Genetic Algorithm to Optimise Schaffer's F6 Function by Dean Kayton
A basic GA with a real-time plotting of evaluation funtion inputs and outputs

[fitness,sel]=f6FitSel(f6EvalFun,popSize) 
function [fitness,sel]=f6FitSel(f6EvalFun,popSize)

%%% RANKED FITNESS %%%%
sortedMasses=sort(f6EvalFun);
for a=1:popSize
    for b=1:popSize
        if f6EvalFun(a)==sortedMasses(b)
            rankOrder(a,:)=b;
        end
    end
end
fitness=rankOrder;

% %%% UNRANKED FITNESS %%%%
% fitness=f6EvalFun;

%Selection
prob = fitness./sum(fitness);
cumprob=cumsum(prob);
selNo=rand(popSize,1);
sel=zeros(popSize,1);
for k=1:popSize
    sel(k,1)=find(cumprob>=selNo(k,1)==1,1);
end

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