人工鱼群算法源代码.docx
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人工鱼群算法源代码.docx
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人工鱼群算法源代码
人工鱼群算法源代码
%人工鱼群算法;formatlong;Visual=2.5;;Step=0.3;;N=50;;Try_number=50;;a1=-10;;b1=10;;a2=-10;;b2=10;;d=[];;h=1e-1;;Friend_number=50;;k=0;;m=50;;X1=rand(N,1)*(b1-a1)+a1;;X2=rand(N,1)*(b2-a2)
%人工鱼群算法
formatlong
Visual=2.5;
Step=0.3;
N=50;
Try_number=50;
a1=-10;
b1=10;
a2=-10;
b2=10;
d=[];
h=1e-1;
Friend_number=50;
k=0;
m=50;
X1=rand(N,1)*(b1-a1)+a1;
X2=rand(N,1)*(b2-a2)+a2;
X=[X1X2];%人工鱼数量
fori=1:
N
wwww=[X(i,1),X(i,2)];
d(i)=maxf(wwww);
end
[w,i]=max(d);
maxX=[X(i,1),X(i,2)];%初始公告板记录
maxY=w;%初始公告板记录
figurex=[];
figurey=[];
figurez=[];
figurex(numel(figurex)+1)=maxX
(1);
figurey(numel(figurey)+1)=maxX
(2);
figurez(numel(figurez)+1)=maxY;
kkk=0;
while(k fori=1: N XX=[X(i,1),X(i,2)];%人工鱼当前状态Xi nf=0; Xc=0; forj=1: N%聚群行为开始 XXX=[X(j,1),X(j,2)]; if(norm(XXX-XX) nf=nf+1; Xc=Xc+XXX; end end Xc=Xc/nf; if((maxf(Xc))>maxf(XX)) XXnext1=XX+rand*Step*(Xc-XX)/norm(Xc-XX);if(XXnext1 (1)>b1) XXnext1 (1)=b1; end if(XXnext1 (1) XXnext1 (1)=a1; end if(XXnext1 (2)>b2) XXnext1 (2)=b2; end if(XXnext1 (2) XXnext1 (2)=a2; end else XXnext1=gmjprey(XX,Try_number,Visual,Step);if(XXnext1 (1)>b1) XXnext1 (1)=b1; end if(XXnext1 (1) XXnext1 (1)=a1; end if(XXnext1 (2)>b2) XXnext1 (2)=b2; end if(XXnext1 (2) XXnext1 (2)=a2; end end%聚群行为结束 %maxX=XX;%追尾行为开始 %maxY=maxf(XX); forj=1: Friend_number XXX=[X(j,1),X(j,2)]; if(norm(XXX-XX) maxY=maxf(XXX); end end if((maxY)>maxf(XX)) XXnext2=XX+rand*Step*(maxX-XX)/norm(maxX-XX);if(XXnext2 (1)>b1) XXnext2 (1)=b1; end if(XXnext2 (1) XXnext2 (1)=a1; end if(XXnext2 (2)>b2) XXnext2 (2)=b2; end if(XXnext2 (2) XXnext2 (2)=a2; end else XXnext2=gmjprey(XX,Try_number,Visual,Step);if(XXnext2 (1)>b1) XXnext2 (1)=b1; end if(XXnext2 (1) XXnext2 (1)=a1; end if(XXnext2 (2)>b2) XXnext2 (2)=b2; end if(XXnext2 (2) XXnext2 (2)=a2; end end%追尾行为结束 if(maxf(XXnext1)>maxf(XXnext2)) X(i,1)=XXnext1 (1); X(i,2)=XXnext1 (2); else X(i,1)=XXnext2 (1); X(i,2)=XXnext2 (2); end end%一次迭代结束 fori=1: N XXXX=[X(i,1),X(i,2)]; ifmaxf(XXXX)>maxY maxY=maxf(XXXX); maxX=XXXX; figurex(numel(figurex)+1)=maxX (1);figurey(numel(figurey)+1)=maxX (2);figurez(numel(figurez)+1)=maxY; end end k=k+1;%进入下一次迭代 end maxX maxY plot3(figurex,figurey,figurez) function[XXnext]=gmjprey(XX,Try_number,Visual,Step)pp=0; forj=1: Try_number XXj=XX+rand*Step*Visual; if(maxf(XX) XXnext=XX+rand*Step*(XXj-XX)/norm(XXj-XX);pp=1; break end end if(~pp) XXnext=XX+rand*Step; end functiony=maxf(QQ) y=(sin(QQ (1))/QQ (1))*(sin(QQ (2))/QQ (2)); 人工鱼群算法的仿真程序-matlab23 tic;figure (1);holdon;ezplot('x*sin(10*pi*;%%参数设置;fishnum=50;%生成50只人工鱼;MAXGEN=50;%最多迭代次数;try_number=100;%最多试探次数;visual=1;%感知距离;delta=0.618;%拥挤度因子;step=0.1;%步长;%%初始化鱼群;lb_ub=[-1, tic figure (1);holdon ezplot('x*sin(10*pi*x)+2',[-1,2]); %%参数设置 fishnum=50;%生成50只人工鱼 MAXGEN=50;%最多迭代次数 try_number=100;%最多试探次数 visual=1;%感知距离 delta=0.618;%拥挤度因子 step=0.1;%步长 %%初始化鱼群 lb_ub=[-1,2,1]; X=AF_init(fishnum,lb_ub); LBUB=[]; fori=1: size(lb_ub,1) LBUB=[LBUB;repmat(lb_ub(i,1: 2),lb_ub(i,3),1)]; end gen=1; BestY=-1*ones(1,MAXGEN);%每步中最优的函数值 BestX=-1*ones(1,MAXGEN);%每步中最优的自变量 besty=-100;%最优函数值 Y=AF_foodconsistence(X); whilegen<=MAXGEN fprintf(1,'%d\n',gen) fori=1: fishnum %%聚群行为 [Xi1,Yi1]=AF_swarm(X,i,visual,step,delta,try_number,LBUB,Y);%%追尾行为 [Xi2,Yi2]=AF_follow(X,i,visual,step,delta,try_number,LBUB,Y);ifYi1>Yi2 X(: i)=Xi1; Y(1,i)=Yi1; else X(: i)=Xi2; Y(1,i)=Yi2; end end [Ymax,index]=max(Y); figure (1); plot(X(1,index),Ymax,'.','color',[gen/MAXGEN,0,0]) ifYmax>besty besty=Ymax; bestx=X(: index); BestY(gen)=Ymax; [BestX(: gen)]=X(: index);else BestY(gen)=BestY(gen-1); [BestX(: gen)]=BestX(: gen-1);end gen=gen+1; end plot(bestx (1),besty,'ro','MarkerSize',100)xlabel('x') ylabel('y') title('鱼群算法迭代过程中最优坐标移动') %%优化过程图 figure plot(1: MAXGEN,BestY) xlabel('迭代次数') ylabel('优化值') title('鱼群算法迭代过程') disp(['最优解X: ',num2str(bestx,'%1.5f')])disp(['最优解Y: ',num2str(besty,'%1.5f')])toc
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