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function [Zp,Xp,Yp,LC1,LC2]=GACFA(M,N,Pm)
% GACFA.m
% Genetic Algorithm for Capacity and Flow Assignment
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greensim%--------------------------------------------------------------------------
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load DATA_CFA;
Xp=zeros(14,1);
Yp=zeros(8,3);
LC1=zeros(1,M);
LC2=LC1;
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farm_X=zeros(14,N);
farm_Y=zeros(8,3*N);
for i=1:N
for j=1:2:
RAND=rand;
if RAND>0.
farm_X(j,i)=1;
else
farm_X(j+1,i)=1;
end
end
end
for i=1:N
for j=1:
RAND=rand;
if RAND<1/
farm_Y(j,3*i-2)=1;
elseif RAND>2/
farm_Y(j,3*i)=1;
else
farm_Y(j,3*i-1)=1;
end
end
end
counter=0;%
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while counter<M%
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newfarm_X=zeros(14,N);
newfarm_Y=zeros(8,3*N);
Ser=randperm(N);
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for i=1:2:(N-1)
A_X=farm_X(:,Ser(i));
B_X=farm_X(:,Ser(i+1));
cp=2*unidrnd(6);
a_X=[A_X(1:cp);B_X((cp+1):end)];
b_X=[B_X(1:cp);A_X((cp+1):end)];
newfarm_X(:,i)=a_X;
newfarm_X(:,i+1)=b_X;
end
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for i=1:2:(N-1)
A_Y=farm_Y(:,(3Ser(i)-2):(3Ser(i)));
B_Y=farm_Y(:,(3Ser(i+1)-2):(3Ser(i+1)));
cp=unidrnd(7);
a_Y=[A_Y(1:cp,:);B_Y((cp+1):end,:)];
b_Y=[B_Y(1:cp,:);A_Y((cp+1):end,:)];
newfarm_Y(:,(3i-2):(3i))=a_Y;
newfarm_Y(:,(3i+1):(3i+3))=b_Y;
end
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FARM_X=[farm_X,newfarm_X];
FARM_Y=[farm_Y,newfarm_Y];
end
pos2=unidrnd(8);
GT_Y(pos2,:)=zeros(1,3);
GT_Y(pos2,unidrnd(3))=1;
end
end
counter=counter+
end
Xp=Xp';
Yp=Yp';
%plot(LC1)
%hold on
plot(LC2)
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function [BestPop,Trace]=fga
(FUN,LB,UB,eranum,popsize,pCross,pMutation,pInversion,options)
% [BestPop,Trace]=fmaxga
(FUN,LB,UB,eranum,popsize,pcross,pmutation)
% Finds a maximum of a function of several variables.
% fmaxga solves problems of the form:
% max F(X) subject to: LB <= X <= UB
% BestPop -
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% popsize -
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% pcross -
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% pmutation -
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% pInversion -
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% options - 1*
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T1=clock;
if nargin<3, error('FMAXGA requires at least three input arguments');
end
if nargin==3,
eranum=200;popsize=100;pCross=0.8;pMutation=0.1;pInversion=0.
5;options=[0 1e-4];end
if nargin==4,
popsize=100;pCross=0.8;pMutation=0.1;pInversion=0.15;options=[
1e-4];end
if nargin==5, pCross=0.8;pMutation=0.1;pInversion=0.15;options=[
1e-4];end
if nargin==6, pMutation=0.1;pInversion=0.15;options=[0 1e-4];end
if nargin==7, pInversion=0.15;options=[0 1e-4];end
if find((LB-UB)>0)
error('
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end
s=sprintf('
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4 9......',(eranum*popsize/1000));
disp(s);
global m n NewPop children1 children2 VarNum
bounds=[LB;UB]';bits=[];VarNum=size(bounds,1);
precision=options(2);%
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bits=ceil(log2((bounds(:,2)-bounds(:,1))' ./ precision));%
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[Pop]=InitPopGray(popsize,bits);%
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[m,n]=size(Pop);
NewPop=zeros(m,n);
children1=zeros(1,n);
children2=zeros(1,n);
pm0=pMutation;
BestPop=zeros(eranum,n);%
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Trace=zeros(eranum,length(bits)+1);
i=1;
while i<=eranum
for j=1:m
value(j)=feval(FUN(1,:),(b2f(Pop(j,:),bounds,bits)));%
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end
[MaxValue,Index]=max(value);
BestPop(i,:)=Pop(Index,:);
Trace(i,1)=MaxValue;
Trace(i,(2:length(bits)+1))=b2f(BestPop(i,:),bounds,bits);
%R
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function [R,Rlength]=geneticTSP(D,n,C,m,alpha)
[N,NN]=size(D);
farm=zeros(n,N);%
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for i=1:n
farm(i,=randperm(N);%
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end
R=farm(1,;%
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len=zeros(n,1);%
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fitness=zeros(n,1);%
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counter=0;
while counter<C
for i=1:n
len(i,1)=myLength(D,farm(i,);%
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end
maxlen=max(len);
minlen=min(len);
fitness=fit(len,m,maxlen,minlen);%
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rr=find(len==minlen);
R=farm(rr(1,1),;%
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FARM=farm;%
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nn=0;
for i=1:n
if fitness(i,1)>=alpha*rand
nn=nn+1;
FARM(nn,=farm(i,;
end
end
FARM=FARM(1:nn,;
[aa,bb]=size(FARM);%
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while aa<n
if nn<=
nnper=randperm(2);
else
nnper=randperm(nn);
end
A=FARM(nnper(1),;
B=FARM(nnper(2),;
[A,B]=intercross(A,B);
FARM=[FARM;A;B];
[aa,bb]=size(FARM);
end
if aa>n
FARM=FARM(1:n,;%
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end
farm=FARM;
clear FARM
counter=counter+
end
Rlength=myLength(D,R);
function [a,b]=intercross(a,b)
L=length(a);
if L<=10%
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W=1;
elseif ((L/10)-floor(L/10))>=rand&&L>
W=ceil(L/10);
else
W=floor(L/10);
end
p=unidrnd(L-W+1);%
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for i=1:W%
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x=find(a==b(1,p+i-1));
y=find(b==a(1,p+i-1));
[a(1,p+i-1),b(1,p+i-1)]=exchange(a(1,p+i-1),b(1,p+i-1));
[a(1,x),b(1,y)]=exchange(a(1,x),b(1,y));
end
function [x,y]=exchange(x,y)
temp=x;
x=y;
y=temp;
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function len=myLength(D,p)
[N,NN]=size(D);
len=D(p(1,N),p(1,1));
for i=1N-1)
len=len+D(p(1,i),p(1,i+1));
end
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function fitness=fit(len,m,maxlen,minlen)
fitness=len;
for i=1:length(len)
fitness(i,1)=(1-((len(i,1)-minlen)/(maxlen-minlen+0.000001))).^m;
x(:,1)=[m:-1:1]';
[y x(:,2)]=sort(selectprob);
r=q/(1-(1-q)^m);%
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newfit(x(:,2))=r*(1-q).^(x(:,1)-1);%
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newfit=cumsum(newfit);%
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rNums=sort(rand(m,1));
fitIn=1;newIn=1;
while newIn<=m
if rNums(newIn)<newfit(fitIn)
selectpop(newIn,:)=pop(fitIn,:);
newIn=newIn+1;
else
fitIn=fitIn+1;
end
end
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function [NewPop]=CrossOver(OldPop,pCross,opts)
%OldPop
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global m n NewPop
r=rand(1,m);
y1=find(r<pCross);
y2=find(r>=pCross);
len=length(y1);
if len>2&mod(len,2)==1%
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y2(length(y2)+1)=y1(len);
y1(len)=[];
end
if length(y1)>=
for i=0:2:length(y1)-
if opts==
[NewPop(y1(i+1),:),NewPop(y1(i+2),:)]=EqualCrossOver(OldPop
(y1(i+1),:),OldPop(y1(i+2),:));
else
[NewPop(y1(i+1),:),NewPop(y1(i+2),:)]=MultiPointCross(OldPop
(y1(i+1),:),OldPop(y1(i+2),:));
end
end
end
NewPop(y2,:)=OldPop(y2,:);
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function [children1,children2]=EqualCrossOver(parent1,parent2)
global n children1 children
hidecode=round(rand(1,n));%
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crossposition=find(hidecode==1);
holdposition=find(hidecode==0);
children1(crossposition)=parent1(crossposition);%
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children1(holdposition)=parent2(holdposition);%
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children2(crossposition)=parent2(crossposition);%
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children2(holdposition)=parent1(holdposition);%
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function [Children1,Children2]=MultiPointCross(Parent1,Parent2)
global n Children1 Children2 VarNum
Children1=Parent1;
Children2=Parent2;
Points=sort(unidrnd(n,1,2*VarNum));
for i=1:VarNum
Children1(Points(2i-1):Points(2i))=Parent2(Points(2*i-1):Points
(2*i));
Children2(Points(2i-1):Points(2i))=Parent1(Points(2*i-1):Points
(2*i));
end
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function [NewPop]=Mutation(OldPop,pMutation,VarNum)
global m n NewPop
r=rand(1,m);
position=find(r<=pMutation);
len=length(position);
if len>=
for i=1:len
k=unidrnd(n,1,VarNum); %
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for j=1:length(k)
if OldPop(position(i),k(j))==
OldPop(position(i),k(j))=0;
else
OldPop(position(i),k(j))=1;
end
end
end
end
NewPop=OldPop;
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function [NewPop]=Inversion(OldPop,pInversion)
