混合算法求解作业调度问题并采用了自适应函数

clear all clc MaxGen=input('请输入最大进化代数MaxGen='); popsize=input('请输入种群规模popsize='); pr=input('请输入初始接受概率pr='); dd=input('请输入退火控制值dd='); w=[0.2 0.2 0.2 0.2 0.2 0.3 0.2 0.3 0.2 0.3 0.2 0.2 0.3 0.2]; u=[0.8 0.8 0.8 0.8 0.8 0.7 0.8 0.7 0.8 0.7 0.8 0.8 0.7 0.8]; M=[1 6 5 4; 1 6 4 -1; 1 -1 -1 -1; 1 5 4 -1; 1 3 -1 -1; 1 3 4 -1; 1 3 4 -1; 1 3 4 -1; 2 4 -1 -1; 1 3 4 -1; 1 6 5 4; 1 3 4 -1; 1 3 4 -1; 2 4 -1 -1]; pt=[10 15 10 20; 15 30 25 0; 23 0 0 0; 15 15 40 0; 23 20 0 0; 12 20 30 0; 15 60 20 0; 5 30 25 0; 20 30 0 0; 24 18 20 0; 18 24 24 40; 25 40 20 0; 17 20 50 0; 10 50 0 0]; WNumber=39; PNumber=14; MNumber=6; solution=zeros(1,WNumber); k=1; for i=1:14 for j=1:4 if M(i,j)~=-1 solution(k)=i; k=k+1; end end end L=length(solution); Nchange=200; chrompop=repmat(solution,popsize,1); for i=2:popsize for t=1:Nchange changerand=ceil(L*rand(1,2)); temp=chrompop(i,changerand(1)); chrompop(i,changerand(1))=chrompop(i,changerand(2)); chrompop(i,changerand(2))=temp; end end G2=MaxGen-round(0.618*MaxGen); G1=G2-round(0.618*G2); for s=1:popsize fitness(s)=decomyque(chrompop(s,:),M,pt); end max_fitness=max(fitness); min_fitness=min(fitness); avg_fitness=mean(fitness); t0=-((max_fitness-min_fitness)/log(pr)) t=t0 best_fitness=max_fitness s=find(fitness==max_fitness); best_solution=chrompop(min(s),:) for i=1:MaxGen maxfitness(i)=max(fitness); selectset=zeros(popsize,L); selectfitness=zeros(1,popsize); sumfitness=sum(fitness); cumsumfitness=cumsum(fitness); dividesum=cumsumfitness/sumfitness; selectrand=rand(1,popsize); for s=1:popsize if selectrand(s)<dividesum(1) selectset(s,:)=chrompop(1,:); selectfitness(s)=fitness(1); end for s_1=2:popsize if dividesum(s_1-1)<selectrand(s)&selectrand(s)<dividesum(s_1); selectset(s,:)=chrompop(s_1,:); selectfitness(s)=fitness(s_1); break; end end end if best_fitness<=max(selectfitness) best_fitness=max(selectfitness); s=find(selectfitness==max(selectfitness)); best_solution=selectset(min(s),:); else randnumber=ceil(rand*popsize); selectset(randnumber,:)=best_solution; selectfitness(randnumber)=best_fitness; end crossset=zeros(popsize,L); %定义交叉后染色体群为crossset crossfitness=zeros(1,popsize); matchrand=randperm(popsize); for s=1:popsize/2 crossrand=rand; if crossrand>0.7 %若随机数大于交叉概率则不交叉，直接放入crossset中 crossset(s,:)=selectset(matchrand(s),:); crossfitness(s)=selectfitness(matchrand(s)); crossset(popsize+1-s,:)=selectset(matchrand(popsize+1-s),:); crossfitness(popsize+1-s)=selectfitness(matchrand(popsize+1-s)); crossfitness(s)=decomyque(crossset(s,:),M,pt); crossfitness(popsize+1-s)=decomyque(crossset(popsize+1-s,:),M,pt); else wayrand=rand; if wayrand<=0.5 crossset(s,:)=selectset(matchrand(s),:); a=crossset(s,:); crossset(popsize+1-s,:)=selectset(matchrand(popsize+1-s),:); b=crossset(popsize+1-s,:); bl=round(rand()*5)+10; ba_start=ceil(rand()*(WNumber-bl)); bb_start=ceil(rand()*(WNumber-bl)); while(ba_start==bb_start) bb_start=ceil(rand()*(WNumber-bl)); end ba=a(1,ba_start:(ba_start+bl)); bb=b(1,bb_start:(bb_start+bl)); for i=1:bl+1 for k=1:WNumber if(a(1,k)==bb(i)) a(1,k)=0; break; end end end for i=1:bl+1 for k=1:WNumber if(b(1,k)==ba(i)) b(1,k)=0; break; end end end d1=find(a(1,:)); c1=[]; q1=zeros(1,bl+1); for i=1:size(d1,2) c1=[c1 a(1,d1(i))]; w1=[q1 c1]; end d2=find(b(1,:)); c2=[]; q2=zeros(1,bl+1); for j=1:size(d2,2) c2=[c2 b(1,d2(j))]; w2=[q2 c2]; end a(1,:)=[bb c1]; b(1,:)=[ba c2]; crossset(s,:)=a(1,:); crossset(popsize+1-s,:)=b(1,:); crossfitness(s)=decomyque(crossset(s,:),M,pt); crossfitness(popsize+1-s)=decomyque(crossset(popsize+1-s,:),M,pt); else crossset(s,:)=selectset(matchrand(s),:); crossset(popsize+1-s,:)=selectset(matchrand(popsize+1-s),:); s_1=randperm(L); s_2=randperm(L); s_1(5:L)=[]; s_2(5:L)=[]; r_1=sort(s_1); r_2=sort(s_2); tempset_1=crossset(s,r_1(1):r_1(2)); if r_1(3)-r_1(2)==1 crossset(s,r_1(1):(r_1(1)+r_1(4)-r_1(3)))=crossset(s,r_1(3):r_1(4)); crossset(s,r_1(1)+r_1(4)-r_1(3)+1:r_1(4))=tempset_1; else tempset_2=crossset(s,r_1(2)+1:r_1(3)-1); crossset(s,r_1(1):(r_1(1)+r_1(4)-r_1(3)))=crossset(s,r_1(3):r_1(4)); crossset(s,(r_1(1)+r_1(4)-r_1(3)+1):(r_1(1)+r_1(4)-r_1(2)-1))=tempset_2; crossset(s,(r_1(1)+r_1(4)-r_1(2)):r_1(4))=tempset_1; end tempset_1=crossset(popsize+1-s,r_2(1):r_2(2)); if r_2(3)-r_2(2)==1 crossset(popsize+1-s,r_2(1):(r_2(1)+r_2(4)-r_2(3)))=crossset(popsize+1-s,r_2(3):r_2(4)); crossset(popsize+1-s,(r_2(1)+r_2(4)-r_2(3)+1):r_2(4))=tempset_1; else tempset_2=crossset(popsize+1-s,r_2(2)+1:r_2(3)-1); crossset(popsize+1-s,r_2(1):(r_2(1)+r_2(4)-r_2(3)))=crossset(popsize+1-s,r_2(3):r_2(4)); crossset(popsize+1-s,(r_2(1)+r_2(4)-r_2(3)+1):(r_2(1)+r_2(4)-r_2(2)-1))=tempset_2; crossset(popsize+1-s,(r_2(1)+r_2(4)-r_2(2)):r_2(4))=tempset_1; end crossfitness(s)=decomyque(crossset(s,:),M,pt); crossfitness(popsize+1-s)=decomyque(crossset(popsize+1-s,:),M,pt); end end end if best_fitness<=max(crossfitness) best_fitness=max(crossfitness); s=find(crossfitness==max(crossfitness)); best_solution=crossset(min(s),:); else randnumber=ceil(rand*popsize); crossset(randnumber,:)=best_solution; crossfitness(randnumber)=best_fitness; end %变异操作 average_fitness=sum(crossfitness)/popsize; mutationset=zeros(popsize,L); mutationfitness=zeros(1,popsize); for s=1:popsize mutationrand=rand; if mutationrand>0.1 mutationset(s,:)=crossset(s,:); mutationfitness(s)=crossfitness(s); else tempsolution=repmat(crossset(s,:),3,1); tempfitness=zeros(1,3); r=randperm(L); tempset=tempsolution(1,r(1)); %变异方式之一：交换 tempsolution(1,r(1))=tempsolution(1,r(2));