ga.asv

简单遗传算法matlab文件?虻ヒ糯惴╩atlab文件

function Ret=GA(GAPara)
% This is simple genetic algorithm(SGA)
% In this function ,it fulfils genetic algorithm
%*****************************************************
Individuals=struct('Fitness',zeros(1,GAPara.SizePop),...%'value',zeros(1,GAPara.SizePop),...
    'Chrom',[]);                    % structure of population

AvgFitness=[];                      % average fitness of population  
BestFitness=[];                     % best fitness of population
BestChrom=[];                       % chromosome of best fitness
% inivitialization
for i=1:GAPara.SizePop
    % produce new population at random
    Individuals.Chrom(i,:)=Code(GAPara.LenChrom,GAPara.CodeFcn,GAPara.Bound);
    x=Decode(GAPara.LenChrom,GAPara.Bound,Individuals.Chrom(i,:),GAPara.CodeFcn);
    % caculate fitness
    Individuals.Fitness(i)=feval(GAPara.Fcn);
end

% find maximum value which is best
[BestFitness BestIndex]=max(Individuals.Fitness);
BestChrom=Individuals.Chrom(BestIndex,:);
AvgFitness=sum(Individuals.Fitness)/GAPara.SizePop;
% record average and best fitness of every generation
Trace=[AvgFitness BestFitness]; 

% evolution begin
for i=1:GAPara.MaxGen
    % selection
    Individuals=Select(Individuals,GAPara.SizePop,GAPara.SelectFcn);
    % crossover
    Individuals.Chrom=Cross(GAPara.PCross,GAPara.LenChrom,Individuals,...
        GAPara.SizePop,GAPara.CrossFcn,[i GAPara.MaxGen]);
    % mutation
    Individuals.Chrom=Mutation(GAPara.PMutation,GAPara.LenChrom,Individuals,...
        GAPara.SizePop,GAPara.MutationFcn,GAPara.Bound,[i GAPara.MaxGen]);
    
    % calculate fitness  
    for j=1:GAPara.SizePop
        x=Decode(GAPara.LenChrom,GAPara.Bound,Individuals.Chrom(j,:),GAPara.CodeFcn);
        Individuals.Fitness(j)=feval(GAPara.AinFcn);   
    end
    
    % substitute chromosome of worest fitness
    % find maximum value which is best
    [NewBestFitness,NewBestIndex]=max(Individuals.Fitness);
    [WorestFitness,WorestIndex]=min(Individuals.Fitness);
    % substitute chromosome of worest fitness
    if BestFitness<NewBestFitness
        BestFitness=NewBestFitness;
        BestChrom=Individuals.Chrom(NewBestIndex,:);
    end
    Individuals.Chrom(WorestIndex,:)=BestChrom;
    Individuals.Fitness(WorestIndex)=BestFitness;
    
    AvgFitness=sum(Individuals.Fitness)/GAPara.SizePop;
    
    Trace=[Trace;AvgFitness BestFitness];
    if BestFitness<=Para.Goal
        break;
    end
end


% draw fitness of every generation
HFig=findobj('Tag','Trace');
% See if it is open
if ishandle(HFig)
    figure(HFig);
else
    HFig=figure('Tag','Trace');
end
figure(HFig);
[r c]=size(Trace);
plot([1:r]',Trace(:,1),'r-',[1:r]',Trace(:,2),'b--');
title(['适应度曲线  ' '终止代数＝' num2str(maxgen)]);
xlabel('进化代数');ylabel('适应度');
legend('平均适应度','最佳适应度');
disp('适应度                   变量');
x=Decode(lenchrom,bound,bestchrom,fcode);
% show in command window
disp([bestfitness x]);