上傳人：r***

認證信息

認證類型：個人認證

認證主體：閆**（實名認證）

IP屬地：北京

IP屬地：北京 上傳時間：2023-07-04 格式：DOCX 頁數(shù)：19 大?。?4.85KB 積分：12 舉報 版權申訴

遺傳算法程序(一):說明：fga.m為遺傳算法的主程序；采用二進制Gray編碼，采用基于輪盤賭法的非線性排名選擇,均勻交叉,變異操作,而且還引入了倒位操作!function[BestPop,Trace]=fga(FUN,LB,UB,eranum,popsize,pCross,pMutation,pInversion,options)%[BestPop,Trace]=fmaxga(FUN,LB,UB,eranum,popsize,pcross,pmutation)%Findsamaximumofafunctionofseveralvariables.%fmaxgasolvesproblemsoftheform:%maxF(X)subjectto:LB<=X<=UB%BestPop-最優(yōu)的群體即為最優(yōu)的染色體群%Trace-最佳染色體所對應的目標函數(shù)值%FUN-目標函數(shù)%LB-自變量下限%UB-自變量上限%eranum-種群的代數(shù),取100--1000(默認200)%popsize-每一代種群的規(guī)模；此可取50--200(默認100)%pcross-交叉概率,一般取0.5--0.85之間較好(默認0.8)%pmutation-初始變異概率,一般取0.05-0.2之間較好(默認0.1)%pInversion-倒位概率,一般取0.05－0.3之間較好(默認0.2)%options-1*2矩陣,options(1)=0二進制編碼(默認0),option(1)~=0十進制編%碼,option(2)設定求解精度(默認1e-4)%%T1=clock；ifnargin<3,error('FMAXGArequiresatleastthreeinputarguments')；endifnargin==3,eranum=200；popsize=100；pCross=0.8；pMutation=0.1；pInversion=0.15；options=[01e-4]；endifnargin==4,popsize=100；pCross=0.8；pMutation=0.1；pInversion=0.15；options=[01e-4]；endifnargin==5,pCross=0.8；pMutation=0.1；pInversion=0.15；options=[01e-4]；endifnargin==6,pMutation=0.1；pInversion=0.15；options=[01e-4]；endifnargin==7,pInversion=0.15；options=[01e-4]；endiffind((LB-UB)>0)error('數(shù)據(jù)輸入錯誤，請重新輸入(LB<UB):');ends=sprintf('程序運行需要約％.4f秒鐘時間,請稍等',(eranum*popsize/1000));disp(s)；globalmnNewPopchildren1children2VarNumbounds=[LB;UB]';bits=[];VarNum=size(bounds,1);precision=options(2);%由求解精度確定二進制編碼長度bits=ceil(log2((bounds(:,2)-bounds(:,1))'./precision));%由設定精度劃分區(qū)間[Pop]=InitPopGray(popsize,bits);%初始化種群[m,n]=size(Pop);NewPop=zeros(m,n);children1=zeros(1,n);children2=zeros(1,n);pm0=pMutation;BestPop=zeros(eranum,n);%分配初始解空間BestPop,TraceTrace=zeros(eranum,length(bits)+1);i=1;whilei<=eranumforj=1:mvalue(j)=feval(FUN(1,:),(b2f(Pop(j,:),bounds,bits)));%計算適應度end[MaxValue,Index]=max(value);BestPop(i,:)=Pop(Index,:);Trace(i,1)=MaxValue;Trace(i,(2:length(bits)+1))=b2f(BestPop(i,:),bounds,bits);[selectpop]=NonlinearRankSelect(FUN,Pop,bounds,bits);%非線性排名選擇[CrossOverPop]=CrossOver(selectpop,pCross,round(unidrnd(eranum-i)/eranum));%采用多點交叉和均勻交叉，且逐步增大均勻交叉的概率%round(unidrnd(eranum-i)/eranum)[MutationPop]=Mutation(CrossOverPop,pMutation,VarNum);%變異[InversionPop]=Inversion(MutationPop,pInversion);%倒位Pop=InversionPop;%更新pMutation=pm0+(iA4)*(pCross/3-pm0)/(eranumA4);%隨著種群向前進化，逐步增大變異率至1/2交叉率p(i)=pMutation;i=i+1;endt=1:eranum;plot(t,Trace(:,1)');title('函數(shù)優(yōu)化的遺傳算法');xlabel('進化世代數(shù)(eranum)');ylabel('每一代最優(yōu)適應度(maxfitness)');[MaxFval,I]=max(Trace(:,1));X=Trace(I,(2:length(bits)+1));holdon;plot(I,MaxFval,'*');text(I+5,MaxFval,['FMAX='num2str(MaxFval)]);str1=sprintf('進化到%d代,自變量為%s時,得本次求解的最優(yōu)值%f\n對應染色體是：％s',I,num2str(X),MaxFval,num2str(BestPop(I,:)));disp(str1);%figure(2);plot(t,p);%繪制變異值增大過程T2=clock;elapsed_time=T2-T1;ifelapsed_time(6)<0elapsed_time(6)=elapsed_time(6)+60;elapsed_time(5)=elapsed_time(5)-1;endifelapsed_time(5)<0elapsed_time(5)=elapsed_time(5)+60;elapsed_time(4)=elapsed_time(4)-1;end%像這種程序當然不考慮運行上小時啦str2=sprintf('程序運行耗時%d小時%d分鐘%.4f',elapsed_time(4),elapsed_time(5),elapsed_time(6));disp(str2);%初始化種群%采用二進制Gray編碼，其目的是為了克服二進制編碼的Hamming懸崖缺點function[initpop]=InitPopGray(popsize,bits)len=sum(bits);initpop=zeros(popsize,len);%Thewholezeroencodingindividualfori=2:popsize-1pop=round(rand(1,len));pop=mod(([0pop]+[pop0]),2);%i=1時,b(1)=a(1);i>1時,b(i)=mod(a(i-1)+a(i),2)%其中原二進制串:a(1)a(2)...a(n),Gray串:b(1)b(2)...b(n)initpop(i,:)=pop(1:end-1);endinitpop(popsize,:)=ones(1,len);%Thewholeoneencodingindividual%解碼function[fval]=b2f(bval,bounds,bits)%fval-表征各變量的十進制數(shù)%bval-表征各變量的二進制編碼串%bounds-各變量的取值范圍%bits-各變量的二進制編碼長度scale=(bounds(:,2)-bounds(:,1))'./(2.Abits-1);%TherangeofthevariablesnumV=size(bounds,1);cs=[0cumsum(bits)];fori=1:numVa=bval((cs(i)+1):cs(i+1));fval(i)=sum(2C(size(a,2)-1:-1:0).*a)*scale(i)+bounds(i,1);end%選擇操作%采用基于輪盤賭法的非線性排名選擇%各個體成員按適應值從大到小分配選擇概率：%P(i)=(q/1-(1-q)An)*(1-q)Ai,其中P(0)>P(1)>...>P(n),sum(P(i))=1function[selectpop]=NonlinearRankSelect(FUN,pop,bounds,bits)globalmnselectpop=zeros(m,n);fit=zeros(m,1);fori=1:mfit(i)=feval(FUN(1,:),(b2f(pop(i,:),bounds,bits)));%以函數(shù)值為適應值做排名依據(jù)endselectprob=fit/sum(fit);%計算各個體相對適應度(0,1)q=max(selectprob);%選擇最優(yōu)的概率x=zeros(m,2);x(:,1)=[m:-1:1]';[yx(:,2)]=sort(selectprob);r=q/(1-(1-q)Am);%標準分布基值newfit(x(:,2))=r*(1-q)C(x(:,1)-1);%生成選擇概率newfit=cumsum(newfit);%計算各選擇概率之和rNums=sort(rand(m,1));fitIn=1;newIn=1;whilenewIn<=mifrNums(newIn)<newfit(fitIn)selectpop(newIn,:)=pop(fitIn,:);newIn=newIn+1;elsefitIn=fitIn+1;endend%交叉操作function[NewPop]=CrossOver(OldPop,pCross,opts)%OldPop為父代種群，pcross為交叉概率globalmnNewPopr=rand(1,m);y1=find(r<pCross);y2=find(r>=pCross);len=length(y1);iflen>2&mod(len,2)==1%如果用來進行交叉的染色體的條數(shù)為奇數(shù)，將其調(diào)整為偶數(shù)y2(length(y2)+1)=y1(len);y1(len)=[];endiflength(y1)>=2fori=0:2:length(y1)-2ifopts==0[NewPop(y1(i+1),:),NewPop(y1(i+2),:)]=EqualCrossOver(OldPop(y1(i+1),:),OldPop(y1(i+2),:));else[NewPop(y1(i+1),:),NewPop(y1(i+2),:)]=MultiPointCross(OldPop(y1(i+1),:),OldPop(y1(i+2),:));endendendNewPop(y2,:)=OldPop(y2,:);%采用均勻交叉function[children1,children2]=EqualCrossOver(parent1,parent2)globalnchildren1children2hidecode=round(rand(1,n));%隨機生成掩碼crossposition=find(hidecode==1);holdposition=find(hidecode==0);children1(crossposition)=parent1(crossposition);%掩碼為1,父1為子1提供基因children1(holdposition)=parent2(holdposition);%掩碼為0,父2為子1提供基因children2(crossposition)=parent2(crossposition);%掩碼為1,父2為子2提供基因children2(holdposition)=parent1(holdposition);%掩碼為0,父1為子2提供基因%采用多點交叉，交叉點數(shù)由變量數(shù)決定function[Children1,Children2]=MultiPointCross(Parent1,Parent2)globalnChildren1Children2VarNumChildren1=Parent1;Children2=Parent2;Points=sort(unidrnd(n,1,2*VarNum));fori=1:VarNumChildren1(Points(2*i-1):Points(2*i))=Parent2(Points(2*i-1):Points(2*i));Children2(Points(2*i-1):Points(2*i))=Parent1(Points(2*i-1):Points(2*i));end%變異操作function[NewPop]=Mutation(OldPop,pMutation,VarNum)globalmnNewPopr=rand(1,m);position=find(r<=pMutation);len=length(position);iflen>=1fori=1:lenk=unidrnd(n,1,VarNum);%設置變異點數(shù)，一般設置1點forj=1:length(k)ifOldPop(position(i),k(j))==1OldPop(position(i),k(j))=0;elseOldPop(position(i),k(j))=1;endendendendNewPop=OldPop;%倒位操作function[NewPop]=Inversion(OldPop,pInversion)globalmnNewPopNewPop=OldPop;r=rand(1,m);PopIn=find(r<=pInversion);len=length(PopIn);iflen>=1fori=1:lend=sort(unidrnd(n,1,2));ifd(1)~=1&d(2)~=nNewPop(PopIn(i),1:d(1)-1)=OldPop(PopIn(i),1:d(1)-1);NewPop(PopIn(i),d(1):d(2))=OldPop(PopIn(i),d(2):-1:d(1));NewPop(PopIn(i),d(2)+1:n)=OldPop(PopIn(i),d(2)+1:n);endendend遺傳算法程序(二):functionyouhuafunD=code;N=50;%Tunablemaxgen=50;%Tunablecrossrate=0.5;%Tunablemuterate=0.08;%Tunablegeneration=1;num=length(D);fatherrand=randint(num,N,3);score=zeros(maxgen,N);whilegeneration<=maxgenind=randperm(N-2)+2;%隨機配對交叉A=fatherrand(:,ind(1:(N-2)/2));B=fatherrand(:,ind((N-2)/2+1:end));%多點交叉rnd=rand(num,(N-2)/2);ind=rndtmp=A(ind);A(ind)=B(ind);B(ind)=tmp;%%兩點交叉%%%%%%%rndtmp=randint(1,1,num)+1;tmp=A(1:rndtmp,kk);A(1:rndtmp,kk)=B(1:rndtmp,kk);B(1:rndtmp,kk)=tmp;%endfatherrand=[fatherrand(:,1:2),A,B];%變異rnd=rand(num,N);ind=rnd[m,n]=size(ind);tmp=randint(m,n,2)+1;tmp(:,1:2)=0;fatherrand=tmp+fatherrand;fatherrand=mod(fatherrand,3);%fatherrand(ind)=tmp;%評價、選擇scoreN=scorefun(fatherrand,D);%求得N個個體的評價函數(shù)score(generation,:)=scoreN;[scoreSort,scoreind]=sort(scoreN);sumscore=cumsum(scoreSort);sumscore=sumscore./sumscore(end);childind(1:2)=scoreind(end-1:end);fork=3:Ntmprnd=rand;tmpind=tmprnddifind=[0,diff(tmpind)];if~any(difind)difind(1)=1;endchildind(k)=scoreind(logical(difind));endfatherrand=fatherrand(:,childind);generation=generation+1;end%scoremaxV=max(score,[],2);minV=11*300-maxV;plot(minV,'*');title('各代的目標函數(shù)值')；F4=D(:,4);FF4=F4-fatherrand(:,1);FF4=max(FF4,1);D(:,5)=FF4;saveDDataDfunctionD=codeloadyouhua.mat%propertiesF2andF3F1=A(:,1);F2=A(:,2);F3=A(:,3);if(max(F2)>1450)||(min(F2)<=900)error('DATApropertyF2exceedit''srange(900,1450]')end%getgrouppropertyF1ofdata,accordingtoF2valueF4=zeros(size(F1));forite=11:-1:1index=find(F2<=900+ite*50);F4(index)=ite;endD=[F1,F2,F3,F4];functionScoreN=scorefun(fatherrand,D)F3=D(:,3);

F4=D(:,4);N=size(fatherrand,2);FF4=F4*ones(1,N);FF4rnd=FF4-fatherrand;FF4rnd=max(FF4rnd,1);ScoreN=ones(1,N)*300*11;%這里有待優(yōu)化fork=1:NFF4k=FF4rnd(:,k);forite=1:11F0index=find(FF4k==ite);if~isempty(F0index)tmpMat=F3(F0index);tmpSco=sum(tmpMat);ScoreBin(ite)=mod(tmpSco,300);endendScorek(k)=sum(ScoreBin);endScoreN=ScoreN-Scorek;遺傳算法程序（三）：%最大迭代步數(shù)%最大迭代步數(shù)%當前最大的適應度%停止循環(huán)的適應度%初始取值范圍[0255]%進入加速迭代的間隔%優(yōu)化的次數(shù)MAX_gen=200;best.max_f=0;STOP_f=14.5;RANGE=[0255];SPEEDUP_INTER=5;advance_k=0;popus=init;%初始化forgen=1:MAX_genfitness=fit(popus,RANGE);%求適應度f=fitness.f;picked=choose(popus,fitness);%選擇popus=intercross(popus,picked);%雜交popus=aberrance(popus,picked);%變異ifmax(f)>best.max_fadvance_k=advance_k+1;x_better(advance_k)=fitness.x;best.max_f=max(f);best.popus=popus;best.x=fitness.x;endifmod(advance_k,SPEEDUP_INTER)==0RANGE=minmax(x_better);RANGEadvance=0;endendreturn;functionpopus=init%初始化M=50;%種群個體數(shù)目N=30;%編碼長度popus=round(rand(M,N));return;functionfitness=fit(popus,RANGE)%求適應度[M,N]=size(popus);fitness=zeros(M,1);%適應度f=zeros(M,1);%函數(shù)值A=RANGE(1);B=RANGE(2);%初始取值范圍[0255]form=1:Mx=0;forn=1:Nx=x+popus(m,n)*(2A(n-1));endx=x*((B-A)/(2AN))+A;fork=1:5f(m,1)=f(m,1)-(k*sin((k+1)*x+k));endendf_std=(f-min(f))./(max(f)-min(f));%函數(shù)值標準化fitness.f=f;fitness.f_std=f_std;fitness.x=x;return;functionpicked=choose(popus,fitness)%選擇f=fitness.f;f_std=fitness.f_std;[M,N]=size(popus);choose_N=3;%選擇choose_N對雙親picked=zeros(choose_N,2);%記錄選擇好的雙親p=zeros(M,1);%選擇概率d_order=zeros(M,1);%把父代個體按適應度從大到小排序f_t=sort(f,'descend');%將適應度按降序排列fork=1:Mx=find(f==f_t(k));%降序排列的個體序號d_order(k)=x(1);endform=1:Mpopus_t(m,:)=popus(d_order(m),:);endpopus=popus_t;f=f_t;p=f_std./sum(f_std);%選擇概率c_p=cumsum(p)';%累積概率forcn=1:choose_Npicked(cn,1)=roulette(c_p);%輪盤賭picked(cn,2)=roulette(c_p);%輪盤賭popus=intercross(popus,picked(cn,:));%雜交endpopus=aberrance(popus,picked);%變異return;functionpopus=intercross(popus,picked)%雜交[M_p,N_p]=size(picked);[M,N]=size(popus);forcn=1:M_pp(1)=ceil(rand*N);%生成雜交位置p(2)=ceil(rand*N);p=sort(p);t=popus(picked(cn,1),p(1):p(2));popus(picked(cn,1),p(1):p(2))=popus(picked(cn,2),p(1):p(2));popus(picked(cn,2),p(1):p(2))=t;endreturn;functionpopus=aberrance(popus,picked)%變異P_a=0.05;%變異概率[M,N]=size(popus);[M_p,N_p]=size(picked);U=rand(1,2);forkp=1:M_pifU(2)>=P_a%如果大于變異概率，就不變異continue;endifU(1)>=0.5a=picked(kp,1);elsea=picked(kp,2);endp(1)=ceil(rand*N);%生成變異位置p(2)=ceil(rand*N);ifpopus(a,p(1))==1%01變換popus(a,p(1))=0;elsepopus(a,p(1))=1;endifpopus(a,p(2))==1popus(a,p(2))=0;elsepopus(a,p(2))=1;endendreturn;functionpicked=roulette(c_p)%輪盤賭[M,N]=size(c_p);M=max([MN]);U=rand;ifU<c_p(1)picked=1;return;endform=1:(M-1)ifU>c_p(m)&U<c_p(m+1)picked=m+1;break;endend全方位的兩點雜交、兩點變異的改進的加速遺傳算法（IAGA）遺傳算法優(yōu)化pid參數(shù)matlab程序chap5_4m%GA(GenericAlgorithm)programtooptimizeParametersofPIDclearall;clearall;globalrinyouttimefG=100;Size=30;CodeL=10;MinX(1)=zeros(1);MaxX(1)=20*ones(1);MinX(2)=zeros(1);MaxX(2)=1.0*ones(1);MinX(3)=zeros(1);MaxX(3)=1.0*ones(1);E=round(rand(Size,3*CodeL));%InitianCode!BsJ=0;forkg=1:1:Gtime(kg)=kg;fors=1:1:Sizem=E(s,:);y1=0;y2=0;y3=0;m1=m(1:1:CodeL);fori=1:1:CodeLy1=y1+m1(i)*2A(i-1);endKpid(s,1)=(MaxX(1)-MinX(1))*y1/1023+MinX(1);m2=m(CodeL+1:1:2*CodeL);fori=1:1:CodeLy2=y2+m2(i)*2A(i-1);endKpid(s,2)=(MaxX(2)-MinX(2))*y2/1023+MinX(2);m3=m(2*CodeL+1:1:3*CodeL);fori=1:1:CodeLy3=y3+m3(i)*2A(i-1);endKpid(s,3)=(MaxX(3)-MinX(3))*y3/1023+MinX(3);%*******Step1:EvaluateBestJ*******Kpidi=Kpid(s,:);[Kpidi,BsJ]=chap5_3f(Kpidi,BsJ);BsJi(s)=BsJ;end[OderJi,IndexJi]=sort(BsJi);BestJ(kg)=OderJi(1);BJ=BestJ(kg);Ji=BsJi+1e-10;fi=1./Ji;%Cm=max(Ji);%fi=Cm-Ji;%Avoidingdevidingzero[Oderfi,Indexfi]=sort(fi);%Arrangingfismalltobigger%Bestfi=Oderfi(Size);%LetBestfi=max(fi)%BestS=Kpid(Indexfi(Size),:);%LetBestS=E(m),mistheIndexfibelongto%max(fi)Bestfi=Oderfi(Size);%LetBestfi=max(fi)BestS=E(Indexfi(Size),:);%LetBestS=E(m),mistheIndexfibelongtomax(fi)kgBJBestS;%****Step2:SelectandReproductOperation***fi_sum=sum(fi);fi_Size=(Oderfi/fi_sum)*Size;fi_S=floor(fi_Size);%SelectingBiggerfivaluekk=1;fori=1:1:Sizeforj=1:1:fi_S(i)%SelectandReproduceTempE(kk,:)=E(Indexfi(i),:);kk=kk+1;%kkisusedtoreproduceendend%**********Step3:CrossoverOperation******pc=0.06;n=ceil(20*rand);fori=1:2:(Size-1)temp=rand;ifpc>tempforj=n:1:20TempE(i,j)=E(i+1,j);TempE(i+1,j)=E(i,j);endendendTempE(Size,:)=BestS;E=TempE;%***************Step4:MutationOperation**************%pm=0.001;pm=0.001-[1:1:Size]*(