wenhua.zip_cultural algorithm_文化算法_文化群

%文化算法源程序 clear all close all %初始化算法参数 m=10; n=1; Nmax=50; xrange=[-5 5]; kv=0.1; xspan=xrange(2)-xrange(1); vrange=[-kv*xspan kv*xspan]; c1=2; c2=2; fixp=0.2; X=zeros(m,n); V=zeros(m,n); gbest=zeros(Nmax,n); gbestf=zeros(Nmax,n); av=zeros(Nmax,n); VN=zeros(n,4); N=1; fv=zeros(m,1); %初始化粒子位置、速度 for i=1:m for j=1:n X(i,j)=xrange(1)+rand*(xrange(2)-xrange(1)); V(i,j)=vrange(1)+rand*(vrange(2)-vrange(1)); end fv(i,1)=X(i,1)+5*sin(5*X(i,1))+7*cos(2*X(i,1)); end pbest=X; pbestf=fv; gbestf(N,1)=min(pbestf); findp=find(pbestf==gbestf(N,1)); gbest(N,n)=pbest(findp(1)); gb=gbest(N,n); gbv=gbestf(N,1); av(N,1)=mean(fv); bestN=1; %初始化信都空间 Naccept=ceil((fixp+fixp/N)*m); acceptpool=zeros(1,Naccept); acceptX=zeros(Naccept,n); acceptf=fv; fvmax=max(acceptf); fvmin=min(acceptf); findnum=find(acceptf==fvmin); acceptpool(1)=findnum(1); acceptX(1,:)=X(acceptpool(1),:); acceptf(acceptpool(1))=fvmax; for i=2:Naccept fvmin=min(acceptf); findnum=find(acceptf==fvmin); acceptpool(i)=findnum(1); acceptX(i,:)=X(acceptpool(i),:); acceptf(acceptpool(i))=fvmax; end for i=1:n lowv=min(acceptX(:,i)); lower1=find(X(:,i)==lowv); lower=lower1(1); VN(i,1)=X(lower,i); VN(i,3)=fv(lower); upv=max(acceptX(:,i)); uper1=find(X(:,i)==upv); uper=uper1(1); VN(i,2)=X(uper,i); VN(i,4)=fv(uper); end %循环迭代 for N=2:Nmax for j=1:n xspan=abs(VN(j,2)-VN(j,1)); vrange=[-kv*xspan kv*xspan]; for i=1:m V(i,j)=V(i,j)+c1*rand*(pbest(i,j)-X(i,j))+c2*rand*(gb(1,j)-X(i,j)); if V(i,j)<vrange(1) V(i,j)=vrange(1); elseif V(i,j)>vrange(2) V(i,j)=vrange(2); end if X(i,j)<VN(1,3) X(i,j)=X(i,j)+abs(V(i,j)); elseif X(i,j)>VN(1,4) X(i,j)=X(i,j)-abs(V(i,j)); else X(i,j)=X(i,j)+V(i,j); end end if X(i,j)<xrange(1) X(i,j)=xrange(1); elseif X(i,j)>xrange(2) X(i,j)=xrange(2); end end end %计算每个粒子的适应度值 for i=1:m fv(i,1)=X(i,1)+5*sin(5*X(i,1))+7*cos(2*X(i,1)); if fv(i,1)<pbestf(i,1) pbestf(i,1)=fv(i,1); pbest(i,1)=X(i,1); end end %更新全局最优 minpbf=min(pbestf) if minpbf<gbv gbv=minpbf findp=find(pbestf==gbv); gb=pbest(findp(1)); bestN=N; end av(N,1)=mean(fv); gbest(N,1)=gb; gbestf(N,1)=gbv; %每五代更新一次信度空间 if mod(N,5)==0 Naccept=ceil((fixp+fixp/N)*m); acceptpool=zeros(1,Naccept); acceptX=zeros(Naccept,n); acceptf=fv; fvmax=max(acceptf); fvmin=min(acceptf); findnum=find(acceptf==fvmin); acceptpool(1)=findnum(1); acceptX(1,:)=X(acceptpool(1),:); acceptf(acceptpool(1))=fvmax; for i=2:Naccept fvmin=min(acceptf); findnum=find(acceptf==fvmin); acceptpool(i)=findnum(1); acceptX(i,:)=X(acceptpool(i),:); acceptf(acceptpool(i))=fvmax; end for i=1:n lowv=min(acceptX(:,i)); lower1=find(X(:,i)==lowv); lower=lower1(1); if (X(lower,i)<VN(i,1))||(fv(lower)<VN(i,3)) VN(i,1)=X(lower,i); VN(i,3)=fv(lower); end upv=max(acceptX(:,i)); uper1=find(X(:,i)==upv); uper=uper1(1); if (X(uper,i)>VN(i,2))||(fv(uper)<VN(i,4)) VN(i,2)=X(uper,i); VN(i,4)=fv(uper); end end end bestN gbv figure(1) n=1:Nmax plot(n,gbestf,n,gbestf) title('global best fitness of each iteration') figure(2) n=1:Nmax; plot(n,av,n,av) title('average fitness of each iteration')