iterative.m

用4个种群来优化函数

function [individuals,avgfitness,bestfitness,bestchrom] = iterative(individuals,maxgen,sizepop,fselect,fcode,pcross,fcross,pmutation,fmutation,lenchrom,bound,bestfitness,bestchrom)
%对每个种群进行100次遗传算法操作
%参数参看main函数
%
%
%编写日期 2008.4.5

% 进化开始
for i=1:maxgen
    % 选择
    individuals=Select(individuals,sizepop,fselect); 
    avgfitness=sum(individuals.fitness)/sizepop;
    %交叉
    individuals.chrom=Cross(pcross,lenchrom,individuals.chrom,sizepop,fcross,[i maxgen],fcode,bound);
    % 变异
    individuals.chrom=Mutation(pmutation,lenchrom,individuals.chrom,sizepop,fmutation,[i maxgen],fcode,bound);
    
    % 计算适应度 
    for j=1:sizepop
        x=Decode(lenchrom,bound,individuals.chrom(j,:),fcode); %解码
        % 修改处
        %individuals.fitness(j)=AimFunc(x,heli,id_data,0);
        individuals.fitness(j)=Aimfunc(x);   
    end
    
  %找到最小和最大适应度的染色体及它们在种群中的位置
    [newbestfitness,newbestindex]=min(individuals.fitness);
    [worestfitness,worestindex]=max(individuals.fitness);
    % 代替上一次进化中最好的染色体
    if bestfitness>newbestfitness
        bestfitness=newbestfitness;
        bestchrom=individuals.chrom(newbestindex,:);
    end
    individuals.chrom(worestindex,:)=bestchrom;
    individuals.fitness(worestindex)=bestfitness;
    
    avgfitness=sum(individuals.fitness)/sizepop;
    
 %   trace=[trace;avgfitness bestfitness]; %记录每一代进化中最好的适应度和平均适应度
end
%进化结束
trace=[avgfitness bestfitness];