遗传算法matlab实现源程序

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1、附页：一．遗传算法源程序：clc;clear;population;%评价目标函数值foruim=1:popsize   vector=population(uim,:);   obj(uim)=hanshu(hromlength,vector,phen);end%obj%min(obj)clearuim;objmin=min(obj);forsequ=1:popsize   ifobj(sequ)==objmin       opti=population(sequ,:);   endendclearsequ;fmax=22000;%==forgen=1:maxg

2、en%选择操作%将求最小值的函数转化为适应度函数forindivi=1:popsize   obj1(indivi)=1/obj(indivi);endclearindivi;%适应度函数累加总合total=0;forindivi=1:popsize   total=total+obj1(indivi);endclearindivi;%每条染色体被选中的几率forindivi=1:popsize   fitness1(indivi)=obj1(indivi)/total;endclearindivi;%各条染色体被选中的范围forindivi=1:popsize  

3、 fitness(indivi)=0;   forj=1:indivi       fitness(indivi)=fitness(indivi)+fitness1(j);   endendclearj;fitness;%选择适应度高的个体forranseti=1:popsize   ran=rand;   while(ran>1

4、

5、ran<0)       ran=rand;   end   ran;   ifran<=fitness(1)       newpopulation(ranseti,:)=population(1,:);   else       f

6、orfet=2:popsize           if(ran>fitness(fet-1))&&(ran<=fitness(fet))               newpopulation(ranseti,:)=population(fet,:);           end       end   endendclearran;newpopulation;%交叉forint=1:2:popsize-1   popmoth=newpopulation(int,:);                        popfath=newpopulation(in

7、t+1,:);                    popcross(int,:)=popmoth;   popcross(int+1,:)=popfath;   randnum=rand;   if(randnum

       cpoint1=round(rand*hromlength);                cpoint2=round(rand*hromlength);                  while(cpoint2==cpoint1)                            cpoint2=round(rand*h

8、romlength);       end       ifcpoint1>cpoint2                                tem=cpoint1;           cpoint1=cpoint2;           cpoint2=tem;       end       cpoint1;       cpoint2;       forterm=cpoint1+1:cpoint2                              forss=1:hromlength               ifpopcross(i

9、nt,ss)==popfath(term)                   tem1=popcross(int,ss);                   popcross(int,ss)=popcross(int,term);                   popcross(int,term)=tem1;               end           end           cleartem1;       end       forterm=cpoint1+1:cpoint2