npso.asv

粒子群优化算法用于天线阵列方向图综合

%neighbour PSO
%fitness

%initialize
name='De Jong';
if strcmp(name,'De Jong') 
    itmax=1000;
    M=20;
    D=2;
    Vmax=zeros(itmax,1);
    Vmax(1)=2.048;
    Vmin=-2.048;
    Xmax=2.048;
    Xmin=-2.048;
    Opt=[1;1];
    Optvalue=3905.3;
elseif strcmp(fname,'Goldstein')
     itmax=1000;
    M=20;
    D=2;
    Vmax=zeros(itmax,1);
    Vmax(1)=2;
    Vmin=-2;
    Xmax=2;
    Xmin=-2;
    Opt=[0;-1];
    Optvalue=3;   
elseif strcmp(fname,'Branin')
     itmax=1000;
    M=20;
    D=2;
    Vmax=zeros(itmax,1);
    Vmax(1)=5;
    Vmin=-5;
    Xmax=10;
    Xmin=-5;
    Opt=[-22/7;12.275];
    Optvalue=0.3977272;   
elseif strcmp(fname,'Martin')
     itmax=1000;
    M=20;
    D=2;
    Vmax=zeros(itmax,1);
    Vmax(1)=10;
    Vmin=0;
    Xmax=10;
    Xmin=0;
    Opt=[5;5];
    Optvalue=0;   
elseif strcmp(fname,'Rosenbrock')
     itmax=1000;
    M=20;
    D=2;
    Vmax=zeros(itmax,1);
    Vmax(1)=1.2;
    Vmin=-1.2;
    Xmax=1.2;
    Xmin=-1.2;
    Opt=[1;1];
    Optvalue=0;   
elseif strcmp(fname,'Hyper sphere')
    itmax=1000;
    M=20;
    D=6;
    Vmax=zeros(itmax,1);
    Vmax(1)=5.12;
    Vmin=-5.12;
    Xmax=5.12;
    Xmin=-5.12;
    Opt=[0;0;0;0;0;0];
    Optvalue=0;    
end
trial=1;
X=zeros(D,M,itmax);
FX=zeros(itmax,M);
V=zeros(D,M,itmax);  
Pbest=zeros(D,M,itmax);
Gbest=zeros(itmax,D);
Nbest=zeros(itmax,D);
FPbest=zeros(itmax,M);
FGbest=zeros(itmax,1);
FNbest=zeros(itmax,1);
for i=1:M
    X(:,i,1)=(Xmax-Xmin)*randn(D,1)+Xmin.*ones(D,1); 
    FX(1,i)=Fitness(name,X(:,i,1));
    V(:,i,1)=(Vmax(1)-Vmin)*randn(D,1)+Vmin.*ones(D,1);
    Pbest(:,i,1)=X(:,i,1);
    FPbest(1,i)=FX(1,i);
end
[FGbest(1),id]=max(FPbest(1,:));
Gbest(1,:)=Pbest(:,id,1);
w=zeros(itmax,1);
c1=zeros(itmax,1);
c2=zeros(itmax,1);
c3=1;
wmax=0.9;
wmin=0.4;
c1max=2.5;
c1min=0.5;
c2max=c1max;
c2min=c1min;
w(1)=wmax-(wmax-wmin)/(0.75*itmax);
c1(1)=c1max-(c1max-c1min)/itmax;
c2(1)=c2min+(c2max-c2min)/itmax;
    
Threshold=0.001;
Xbest=zeros(D,1);
Xbest=X(:,1,1);
FXbest=FX(1,1);
Fdr=zeros(M,1);
    
AvgTr=zeros(trial,1);
%main body
for j=1:trial
for t=2:itmax
    for i=1:M
       for d=1:D
           l=1;
           while(l<M && l~=i)
               Fdr(l)=(Fitness(name,Pbest(:,l,t-1))-Fitness(name,X(:,i,t-1)))/(0.001+abs(Pbest(d,l,t-1)-X(d,i,t-1)));
               l=l+1;
           end
           [Nbest(t-1,:),id]=max(Fdr);
           FNbest(t-1)=FX(t-1,id);
           V(d,i,t)=w(t)*V(d,i,t-1)+c1(t-1)*rand()*(Pbest(t-1,i,d)-X(t-1,i,d))+c2(t-1)*rand()*(Gbest(t-1,d)-X(t-1,i,d))+c3*(Nbest(t-1,d)-X(t-1,i,d));
           V(t,i,d)=min([Vmax(t-1),max([-Vmax(t-1),V(t,i,d)])]);
           X(t,i,d)=min([Xmax,max([Xmin,X(t-1,i,d)+V(t,i,d)])]);
       end
       FX(t,i)=Fitness(name,X(t,i,:));
       if FX(t,i)>FPbest(t-1,i)
           Pbest(t,i,:)=X(t,i,:);
           FPbest(t,i)=FX(t,i);
           if FX(t,i)>FGbest(t-1)
               Gbest(t,:)=X(t,i,:);
               FGbest(t)=FX(t,i);
           end
       end  
    end
    if abs(FGbest(t)-Optvalue/Optvalue)<Threshold
        Xbest=Gbest(t,:);
        FXbest=FGbest(t);
        break;
    end
    w(t)=wmax-(wmax-wmin)/(0.75*itmax)*t;
    c1(t)=c1max-(c1max-c1min)/itmax*t;
    c2(t)=c2min+(c2max-c2min)/itmax*t;
end
Xbest=Gbest(t,:);
FXbest=FGbest(t);
AvgTr(j)=t;
end
AvgIter=mean(AvgTr);
%plot result