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ga_code21.m
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ga_code21.m
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%ga 21
function ga_code21(edgenum)
% mainly amended by Chen Zhen, 2012~2016
CiteNum = 12;
BitNum=(CiteNum-1)*CiteNum/2; %you chan choose 10, 30, 50, 75
setglobal();
global Clist CityLoc CityPop;
population_size=300; %初始种群大小
parent_number = 150;
child_num = population_size - parent_number;
gnmax=100; %最大代数
pc=1; %交叉概率
mutation_rate=0.2; %变异概率
%产生初始种群
population=zeros(parent_number,edgenum);
i = 1;
while i <= parent_number
temp = randperm(BitNum);
if test_connected(temp(1:edgenum))==1
population(i,:) = temp(1:edgenum);
i = i+1;
end
end
population=die(population);
%population(1,:) = [57 5 40 60 31 52 41 34 51 46 1 39 6 59 26 58];
length(population)
gn=1;
fopt=zeros(gn,1);
xmax=zeros(gnmax,edgenum);%第几代
scnew=zeros(child_num,edgenum);%孩子
smnew=zeros(child_num,edgenum);%变异，先生孩子，然后变异
while gn<gnmax+1
for j=1:2:child_num
seln=sel(population); %选择操作
scro=cro(population,seln,pc); %交叉操作
scnew(j,:)=scro(1,:);
scnew(j+1,:)=scro(2,:);
smnew(j,:)=mut(scnew(j,:),mutation_rate); %变异操作
smnew(j+1,:)=mut(scnew(j+1,:),mutation_rate);
end
smnew=die(smnew);
population1=[population;smnew]; %产生了新的种群
f=objf(population1); %计算新种群的适应度
% index记录排序后每个值原来的行数
[f, index] = sort(f,'descend') % 将适应度函数值从小到大排序
population = population1(index(1:parent_number), :); % 先保留一部分较优的个体
%记录当前代最好和平均的适应度
%记录当前代的最佳个体
x=population(1,:);
xmax(gn,:)=x;
gn=gn+1;
fopt(gn) = get_value(x);
end
f = get_value(xmax(end,1:edgenum));
show_graph(xmax(end,1:edgenum),f);
plot(fopt);
ylabel('网络价值');
xlabel('迭代次数');
title(['连接数为' num2str(edgenum)]);
pause(0.01);
figure;
end
%------------------------------------------------
%计算所有种群的适应度,返回价值向量和累计概率
function cost=objf(population)
edgenum = size(population,2);
inn=size(population,1); %读取种群大小
cost=zeros(inn,1);
for i=1:inn
cost(i)=get_value(population(i,1:edgenum));
end
cost=cost'; %取距离倒数
end
%--------------------------------------------------
%根据变异概率判断是否变异
function pcc=pro(pc)
test(1:100)=0;
l=round(100*pc);
test(1:l)=1;
n=round(rand*99)+1;
pcc=test(n);
end
%--------------------------------------------------
%“选择”操作
function seln=sel(p)
seln=zeros(2,1);
num = size(p,1);
c1 = randi([1 num]);
c2 = randi([1 num]);
while c1 == c2
c2 = randi([1 num]);
end
seln(1)=c1;
seln(2)=c2;
end
%------------------------------------------------
%“交叉”操作
function scro=cro(population,seln,pc)
edgenum=size(population,2);
pcc=pro(pc); %根据交叉概率决定是否进行交叉操作，1则是，0则否
scro(1,:)=population(seln(1),:);%选择的
scro(2,:)=population(seln(2),:);
if pcc==1
c1 = randi([1 edgenum]);
middle=scro(1,1:c1);
scro(1,1:c1)=scro(2,1:c1);
scro(2,1:c1)=middle;
end
end
%--------------------------------------------------
%“变异”操作
function snnew=mut(snew,mutation_rate)
snnew=snew;
edgenum=size(snew,2);
mutation_ratem=pro(mutation_rate); %根据变异概率决定是否进行变异操作，1则是，0则否
if mutation_ratem==1
c1 = randi([1 edgenum]);
snnew(c1) = randi([1 66]);
end
end
function population = die(population)
global line_info;
delete=[];
delete_index = 1;
row_num = size(population,1)
edge_num = size(population,2)
i = 1;
while i<=row_num
if length(unique(population(i,:)))~=edge_num
delete(delete_index)=i;
delete_index=delete_index+1;
i=i+1;
continue;
end
arr = eye(12);
num =0;
for line_id=1:edge_num
line_index=population(i,line_id);
x=0;y=0;
x = line_info(line_index,1);
y = line_info(line_index,2);
arr(x,y)=1;
num=num+1;
end
arr1 = arr+arr';
%view(biograph(arr,[],'ShowArrows','off','ShowWeights','on'));% 显示图
if ~connected(arr1)
delete(delete_index)=i;
delete_index=delete_index+1;
i=i+1;
continue;
end
i=i+1;
end
population(delete,:)=[]
end