tic

clc,clear

load sj.txt %加载敌方100 个目标的数据

x=sj(:,1:2:8);x=x(:);

y=sj(:,2:2:8);y=y(:);

sj=[x y];

d1=[70,40];

sj0=[d1;sj;d1];

%距离矩阵d

sj=sj0*pi/180;

d=zeros(102);

for i=1:101

for j=i+1:102

temp=cos(sj(i,1)-sj(j,1))*cos(sj(i,2))*cos(sj(j,2))+sin(sj(i,2))*sin(sj(j,2));

d(i,j)=6370*acos(temp);

end

end

d=d+d';L=102;w=50;dai=100;

%通过改良圈算法选取优良父代A

for k=1:w

c=randperm(100);

c1=[1,c+1,102];

flag=1;

while flag>0

flag=0;

for m=1:L-3

for n=m+2:L-1

if d(c1(m),c1(n))+d(c1(m+1),c1(n+1))<d(c1(m),c1(m+1))+d(c1(n),c1(n+1))

flag=1;

c1(m+1:n)=c1(n:-1:m+1);

end

end

end

end

J(k,c1)=1:102;

end

J=J/102;

J(:,1)=0;J(:,102)=1;

rand('state',sum(clock));

%遗传算法实现过程

A=J;

for k=1:dai %产生0～1 间随机数列进行编码

B=A;

c=randperm(w);

%交配产生子代B

for i=1:2:w

F=2+floor(100*rand(1));

temp=B(c(i),F:102);

B(c(i),F:102)=B(c(i+1),F:102);

B(c(i+1),F:102)=temp;

end

%变异产生子代C

by=find(rand(1,w)<0.1);

if length(by)==0

by=floor(w*rand(1))+1;

end

C=A(by,:);

L3=length(by);

for j=1:L3

bw=2+floor(100*rand(1,3));

bw=sort(bw);

C(j,:)=C(j,[1:bw(1)-1,bw(2)+1:bw(3),bw(1):bw(2),bw(3)+1:102]);

end

G=[A;B;C];

TL=size(G,1);

%在父代和子代中选择优良品种作为新的父代

[dd,IX]=sort(G,2);temp(1:TL)=0;

for j=1:TL

for i=1:101

temp(j)=temp(j)+d(IX(j,i),IX(j,i+1));

end

end

[DZ,IZ]=sort(temp);

A=G(IZ(1:w),:);

end

path=IX(IZ(1),:)

long=DZ(1)

toc

xx=sj0(path,1);yy=sj0(path,2);

plot(xx,yy,'-o')

其中，这里：

%在父代和子代中选择优良品种作为新的父代

[dd,IX]=sort(G,2);temp(1:TL)=0;

为什么要sort排序一下？这样得到的IX所包含的路线不就和原来的路线不一样了吗？新手一枚，求解释？！