adapting.m

用遗传算法及佳点集算法测试同一标准函数,普通的遗传算法和佳点集遗传算法的基本思想和不同点

%计算适应值   adapting.m

for i=1:40
  for k=1:2
    Adapt(i,k)=0;
  end
  adapt(i)=0;
end
 
for i=1:40
  for k=1:2
    for j=1:10
        if pop(i,k,j)==1
            Adapt(i,k)=Adapt(i,k)+2^(10-j);
        end
    end
Adapt(i,k)=Adapt(i,k)*0.004-2.048;
  end
    adapt(i)=100*(Adapt(i,1)-Adapt(i,2))^2+(1-Adapt(i,1))^2;
end
 
global adapt_best;
global best_pos;
adapt_best=0;   %最佳个体
best_pos=0;     %最佳个体在种群中的位置
 
for i=1:40
    adapt_ave(G)=adapt_ave(G)+adapt(i);
    if adapt_best<adapt(i)
        adapt_best=adapt(i);
        best_pos=i;
    end
end
if  best_d<adapt_best
   best_pos=i;
   for j=1:2
for i=1:10
          best_individual(j,i)=pop(best_pos,j,i);
      end
end
end
adapt_max(G)=adapt_best;  
adapt_ave(G)=adapt_ave(G)/40;
  
clear i;
clear j;
clear k;