楼主逗呢

matlab遗传算法源代码
function Main()
%定义全局变量
global VariableNum  POPSIZE   MaxGens PXOVER  PMutation

VariableNum=3  %变量个数
POPSIZE=50     %种群大小
MaxGens=1000   %种群代数
PXOVER=0.8     %交叉概率
PMutation=0.2  %变异概率
%读取数据文件
load E:\现代优化算法\遗传算法\bound.txt
VarBound=bound(:,1:2);

global Pop newPop
Pop=zeros(POPSIZE+1,VariableNum);
newPop=zeros(POPSIZE+1,VariableNum);
%初始化种群
for i=1:POPSIZE
    for j=1:VariableNum
        Pop(i,j)=VarBound(j,1)+rand()*(VarBound(j,2)-VarBound(j,1));        
    end
end
%计算适应值
fitnessList=zeros(POPSIZE,1);
for i=1:POPSIZE
    fitnessList(i,1)=fitness(Pop(i,1:VariableNum));
end
%保存最好值和最坏值
Best=zeros(1,VariableNum+1);
Worst=zeros(1,VariableNum+1);
maxvalue=max(fitnessList);
indexMax=find(fitnessList==maxvalue,1,'first');
Best(1,1:VariableNum)=Pop(indexMax,1:VariableNum);
Best(1,VariableNum+1)=maxvalue;
minvalue=min(fitnessList);
indexMin=find(fitnessList==minvalue,1,'first');
Worst(1,1:VariableNum)=Pop(indexMin,1:VariableNum);
Worst(1,VariableNum+1)=minvalue;
genetation=1;
while genetation<MaxGens
    %计算适应度区间
    sumfit=sum(abs(fitnessList));
    relativeFitness=zeros(POPSIZE,1);
    relativeFitness=abs(fitnessList)/sumfit;
    for i=2:POPSIZE
        relativeFitness(i)=relativeFitness(i-1)+relativeFitness(i);
    end
    %选择操作
    newPop=Select(Pop,relativeFitness);
    %交叉操作
    newPop=Xcross(newPop,VariableNum,PXOVER);
    %变异操作
    newPop=Mutation(newPop,VariableNum,PMutation,VarBound);
    %计算新种群适应值
    for i=1:POPSIZE
        fitnessList(i,1)=fitness(newPop(i,1:VariableNum));
    end
    %保存最好值和替换最坏值
    maxvalue=max(fitnessList);
    indexMax=find(fitnessList==maxvalue,1,'first');
    minvalue=min(fitnessList);
    indexMin=find(fitnessList==minvalue,1,'first');
    if Best<maxvalue
        Best(1,1:VariableNum)=newPop(indexMax,1:VariableNum);
        Best(1,VariableNum+1)=maxvalue;
    else
        newPop(indexMin,1:VariableNum)=Best(1,1:VariableNum);
        fitnessList(indexMin,1)=Best(1,VariableNum+1);
    end
    %用子代替换父代
    Pop=newPop;
    genetation=genetation+1;
end
Best

=========================================================

%选择操作

function newPop=Select(Pop,Rfitness)
for i=1:length(Rfitness)
    r=rand();
    index=1;
    for j=1:length(Rfitness)
        if r<=Rfitness(j,1)
            index=j;
            break;
        end
    end
    newPop(i,:)=Pop(index,:);
end
   
======================================

%交叉操作

function newPop=Xcross(Pop,VariableNUM,CrossRate)
point=1;
sizePop=length(Pop);
for i=0:sizePop/2
    Xrate=rand();
    if Xrate<CrossRate  %如果交叉
        first_index=round(rand()*(sizePop-2)+1);
        second_index=round(rand()*(sizePop-2)+1);
        while first_index==second_index   %排除两个个体一样的情况
            second_index=round(rand()*(sizePop-2)+1);
        end
        if VariableNUM>1
           if VariableNUM==2
              point=1;
           else
               point=round(rand()*(VariableNUM-2)+1);
           end
           tempOne=zeros(1,point);
           tempOne(1,1:point)=Pop(first_index,1:point);
           Pop(first_index,1:point)=Pop(second_index,1:point);
           Pop(second_index,1:point)=tempOne(1,1:point);
       end
    end
end
newPop=zeros(size(Pop),1);
newPop=Pop;
   
====================================================

%变异操作

function newPop=Mutation(Pop,VariableNUM,MutationRate,bound)
point=1;
sizePop=length(Pop);
for i=1:sizePop
    for j=1:VariableNUM
        Mrate=rand();
        if Mrate<MutationRate  %如果发生变异
         Pop(i,j)= rand()*(bound(j,2)-bound(j,1))+ bound(j,1);  
        end
    end
end
newPop=zeros(size(Pop),1);
newPop=Pop;

=================================================

%适应值函数或目标函数

%函数 x1^2-x1*x2+x3
function value=fitness(varargin)
n=varargin{1,1};
value=n(1,1)^2-n(1,1)*n(1,2)+n(1,3);

================================================

实例：bound文件

1 10
0 5
10 20