遗传算法---飞机巡航问题

clc,clear
sj0=[53.7121 15.3046 51.1758 0.0322 46.3253 28.2753 30.3313 6.9348 56.5432 21.4188 10.8198 16.2529 22.7891 23.1045 10.1584 12.4819 20.1050 15.4562 1.9451 0.2057 26.4951 22.1221 31.4847 8.9640 26.2418 18.1760 44.0356 13.5401 28.9836 25.9879 38.4722 20.1731 28.2694 29.0011 32.1910 5.8699 36.4863 29.7284 0.9718 28.1477 8.9586 24.6635 16.5618 23.6143 10.5597 15.1178 50.2111 10.2944 8.1519 9.5325 22.1075 18.5569 0.1215 18.8726 48.2077 16.8889 31.9499 17.6309 0.7732 0.4656 47.4134 23.7783 41.8671 3.5667 43.5474 3.9061 53.3524 26.7256 30.8165 13.4595 27.7133 5.0706 23.9222 7.6306 51.9612 22.8511 12.7938 15.7307 4.9568 8.3669 21.5051 24.0909 15.2548 27.2111 6.2070 5.1442 49.2430 16.7044 17.1168 20.0354 34.1688 22.7571 9.4402 3.9200 11.5812 14.5677 52.1181 0.4088 9.5559 11.4219 24.4509 6.5634 26.7213 28.5667 37.5848 16.8474 35.6619 9.9333 24.4654 3.1644 0.7775 6.9576 14.4703 13.6368 19.8660 15.1224 3.1616 4.2428 18.5245 14.3598 58.6849 27.1485 39.5168 16.9371 56.5089 13.7090 52.5211 15.7957 38.4300 8.4648 51.8181 23.0159 8.9983 23.6440 50.1156 23.7816 13.7909 1.9510 34.0574 23.3960 23.0624 8.4319 19.9857 5.7902 40.8801 14.2978 58.8289 14.5229 18.6635 6.7436 52.8423 27.2880 39.9494 29.5114 47.5099 24.0664 10.1121 27.2662 28.7812 27.6659 8.0831 27.6705 9.1556 14.1304 53.7989 0.2199 33.6490 0.3980 1.3496 16.8359 49.9816 6.0828 19.3635 17.6622 36.9545 23.0265 15.7320 19.5697 11.5118 17.3884 44.0398 16.2635 39.7139 28.4203 6.9909 23.1804 38.3392 19.9950 24.6543 19.6057 36.9980 24.3992 4.1591 3.1853 40.1400 20.3030 23.9876 9.4030 41.1084 27.7149 ];       %加载100个目标的数据
x=sj0(:,1:2:8); x=x(:);
y=sj0(:,2:2:8); y=y(:);
sj=[x y]; d1=[70,40]; 
sj=[d1;sj;d1]; sj=sj*pi/180;  %单位化成弧度
d=zeros(102); %距离矩阵d的初始值
for i=1:101
  for j=i+1:102
  d(i,j)=6370*acos(cos(sj(i,1)-sj(j,1))*cos(sj(i,2))*cos(sj(j,2))+sin(sj(i,2))*sin(sj(j,2)));
  end
end
d=d+d'; w=50; g=100; %w为种群的个数,g为进化的代数
rand('state',sum(clock)); %初始化随机数发生器
for k=1:w  %通过改良圈算法选取初始种群
    c=randperm(100); %产生1,...,100的一个全排列 
    c1=[1,c+1,102]; %生成初始解
    for t=1:102 %该层循环是修改圈 
        flag=0; %修改圈退出标志
    for m=1:100
      for n=m+2:101
        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))
           c1(m+1:n)=c1(n:-1:m+1);  flag=1; %修改圈
        end
      end
    end
   if flag==0
      J(k,c1)=1:102; break %记录下较好的解并退出当前层循环
   end
   end
end
J(:,1)=0; J=J/102; %把整数序列转换成[0,1]区间上的实数,即转换成染色体编码
for k=1:g  %该层循环进行遗传算法的操作 
    A=J; %交配产生子代A的初始染色体
    c=randperm(w); %产生下面交叉操作的染色体对 
    for i=1:2:w  
        F=2+floor(100*rand(1)); %产生交叉操作的地址
        temp=A(c(i),[F:102]); %中间变量的保存值
        A(c(i),[F:102])=A(c(i+1),[F:102]); %交叉操作
        A(c(i+1),F:102)=temp;  
    end
    by=[];  %为了防止下面产生空地址,这里先初始化
while ~length(by)
    by=find(rand(1,w)<0.1); %产生变异操作的地址
end
B=A(by,:); %产生变异操作的初始染色体
for j=1:length(by)
   bw=sort(2+floor(100*rand(1,3)));  %产生变异操作的3个地址
   B(j,:)=B(j,[1:bw(1)-1,bw(2)+1:bw(3),bw(1):bw(2),bw(3)+1:102]); %交换位置
end
   G=[J;A;B]; %父代和子代种群合在一起
   [SG,ind1]=sort(G,2); %把染色体翻译成1,...,102的序列ind1
   num=size(G,1); long=zeros(1,num); %路径长度的初始值
   for j=1:num
       for i=1:101
           long(j)=long(j)+d(ind1(j,i),ind1(j,i+1)); %计算每条路径长度
       end
   end
     [slong,ind2]=sort(long); %对路径长度按照从小到大排序
     J=G(ind2(1:w),:); %精选前w个较短的路径对应的染色体
end
path=ind1(ind2(1),:), flong=slong(1)  %解的路径及路径长度
xx=sj(path,1);yy=sj(path,2);
plot(xx,yy,'-o') %画出路径
    原文作者:遗传算法
    原文地址: https://blog.csdn.net/richeylee/article/details/52316001
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