function quantum
% This is quantum genetic algorithm(QGA)
% In this function ,it fulfils quantum genetic algorithm

clc;
clear;



global sizepop  lenchrom
global judge
global maxgen gen

%----------------These can be modified as you like-----------------------
maxgen=500;                         % maximum generation
sizepop=10;                        % size of population 

lenchrom=[8 8];          % length of bit of every varible

pcross=1;
pmutation=0.01;

judge=0;                 % disaster counter
%--------------------------------------------------------------------------
% xx=[];       % 用于存放運行100次的結果
% for internumber=1:50          % 運行10次 

tic;

individuals=struct('fitness',zeros(1,sizepop),...
    'chrom',[]);                    % structure of population
binary=[];
best=struct('fitness',0,'binary',[],'chrom',[]);   % best individual 
avgfitness=[];                      % average fitness of population  


% inivitialization
 for i=1:sizepop*2
    for j=1:sum(lenchrom)
        individuals.chrom(i,j)=1/sqrt(2);
    end 
end


% 量子坍塌
binary=collapse(individuals.chrom,sizepop,lenchrom);

% 求適應度
for i=1:sizepop
    x=binary(i,:);
    individuals.fitness(i)=Aim1(x);        % AimFunc(x) is the function for calculating fitness
end


[best.fitness bestindex]=max(individuals.fitness);     % find maximum value which is best
% record the best individual to "best"
best.binary=binary(bestindex,:);
best.chrom(1,:)=individuals.chrom(2*bestindex-1,:);
best.chrom(2,:)=individuals.chrom(2*bestindex,:);
avgfitness=sum(individuals.fitness)/sizepop;
bestfitness=best.fitness;


% evolution begin
for gen=1:maxgen-1
    
    % disaster
    if judge>0.2*maxgen
       individuals.chrom=disaster(best,sizepop,lenchrom);
   end
    
    % 量子坍塌
    binary=collapse(individuals.chrom,sizepop,lenchrom);

    % calculate fitness  
    for i=1:sizepop
        x=binary(i,:);
        individuals.fitness(i)=Aim1(x);        % AimFunc(x) is the function for calculating fitness
    end  
    
    % quantum cross
   % individuals.chrom=Qcross(pcross,individuals.chrom,sizepop,lenchrom);
    
    % quantum mutation 
    %individuals.chrom=Qmutation(pmutation,individuals.chrom,sizepop,lenchrom);
    
    % quantum gate
    individuals.chrom=Qgate1(individuals,best,binary,sizepop,lenchrom);
    
    
    [newbestfitness,newbestindex]=max(individuals.fitness);    % find maximum value which is best
    % record the best individual to "best"
    if best.fitness<newbestfitness
       best.fitness=newbestfitness;
       best.binary=binary(newbestindex,:);
       best.chrom(1,:)=individuals.chrom(2*bestindex-1,:);
       best.chrom(2,:)=individuals.chrom(2*bestindex,:);
       judge=0;
   else judge=judge+1;     % increase the disaster counter
   end
    avgfitness=[avgfitness;sum(individuals.fitness)/sizepop];
    bestfitness=[bestfitness;best.fitness];
end


% draw fitness of every generation

plot([1:maxgen]',bestfitness,'r-*',[1:maxgen]',avgfitness,'b-o');
title(['適應度曲線  ' '終止代數＝' num2str(maxgen)]);
xlabel('進化代數');ylabel('適應度');
legend('最佳適應度','平均適應度');

disp('適用度 ');
disp([best.fitness]);

toc;

% xx=[xx;best.fitness toc];    % 用于存放運行100次的結果
%end        % 運行100次循環結束
% save xx xx     % 保存運行100次的結果