智能优化算法源代码

人工蚂蚁算法%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function [x,y, minvalue] = AA(func)

% Example [x, y,minvalue] =

AA('Foxhole')

clc;

tic;

subplot(2,2,1); %%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%% plot 1

draw(func);

title([func, ' Function']);

%初始化各参数

Ant=100;%蚂蚁规模

ECHO=200;%迭代次数

step=0.01*rand(1);%局部搜索时的步长temp=[0,0];

%各子区间长度

start1=-100;

end1=100;

start2=-100;

end2=100;

Len1=(end1-start1)/Ant;

Len2=(end2-start2)/Ant;

%P = 0.2;

%初始化蚂蚁位置

for i=1:Ant

X(i,1)=(start1+(end1-start1)*rand(1)); X(i,2)=(start2+(end2-start2)*rand(1)); %func=AA_Foxhole_Func(X(i,1),X(i,2)); val=feval(func,[X(i,1),X(i,2)]);

T0(i)=exp(-val);%初始信息素,随函数值大,信息素浓度小,反之亦

然 %%%%%***************************** ************************************* ***

end; %至此初始化完成

for Echo=1:ECHO %开始寻优

%P0函数定义,P0为全局转移选择因子

a1=0.9;

b1=(1/ECHO)*2*log(1/2);

f1=a1*exp(b1*Echo);

a2=0.225;

b2=(1/ECHO)*2*log(2);

f2=a2*exp(b2*Echo);

if Echo<=(ECHO/2)

P0=f1;

else

P0=f2;

end;

%P函数定义，P为信息素蒸发系数

a3=0.1;

b3=(1/ECHO).*log(9);

P=a3*exp(b3*Echo);

lamda=0.10+(0.14-0.1)*rand(1);%全局转移步长参数

Wmax=1.0+(1.4-1.0)*rand(1);%步长更新参数上限

Wmin=0.2+(0.8-0.2)*rand(1);%步长更新参数下限

%寻找初始最优值

T_Best=T0(1);

for j=1:Ant

if T0(j)>=T_Best

T_Best=T0(j);

BestIndex=j;

end;

end;

W=Wmax-(Wmax-

Wmin)*(Echo/ECHO); %局部搜索步长更新参数

for j_g=1:Ant %全局转移概率求取,当该蚂蚁随在位置不是bestindex时

if j_g~=BestIndex

r=T0(BestIndex)-T0(j_g);

Prob(j_g)=exp(r)/exp(T0(BestIndex));

else%当j_g=BestIndex的时候进行局部搜索

if rand(1)<0.5

1

temp(1,1)=X(BestIndex,1)+W*step;

temp(1,2)=X(BestIndex,2)+W*step;

else

temp(1,1)=X(BestIndex,1)-W*step;

temp(1,2)=X(BestIndex,2)-W*step;

end;

Prob(j_g)=0;%bestindex的蚂蚁不进行全局转移

end;

X1_T=temp(1,1);

X2_T=temp(1,2);

X1_B=X(BestIndex,1);

X2_B=X(BestIndex,2);

%func1 =

AA_Foxhole_Func(X1_T,X2_T); %%%%%%%% %%%********************************** *****************

%F1_T=func1;

F1_T=feval(func,[X(i,1),X(i,2)]);

F1_B=feval(func,[X1_B,X2_B]);

%F1_T=(X1_T-1).^2+(X2_T-2.2).^2+1;

%func2 =

AA_Foxhole_Func(X1_B,X2_B); %%%%%%%%% %%%%********************************* ******************

%F1_B=func2;

%F1_B=(X1_B-1).^2+(X2_B-2.2).^2+1;

if exp(-F1_T)>exp(-F1_B) X(BestIndex,1)=temp(1,1);

X(BestIndex,2)=temp(1,2);

end;

end;

for j_g_tr=1:Ant

if Prob(j_g_tr)

X(j_g_tr,1)=X(j_g_tr,1)+lamda*(X(Best Index,1)-

X(j_g_tr,1));%Xi=Xi+lamda*(Xbest-Xi)

X(j_g_tr,2)=X(j_g_tr,2)+lamda*(X(Best Index,2)-

X(j_g_tr,2));%Xi=Xi+lamda*(Xbest-Xi)

X(j_g_tr,1)=bound(X(j_g_tr,1),start1, end1);

X(j_g_tr,2)=bound(X(j_g_tr,2),start2, end2);

else

X(j_g_tr,1)=X(j_g_tr,1)+((-

1)+2*rand(1))*Len1;%Xi=Xi+rand(-

1,1)*Len1

X(j_g_tr,2)=X(j_g_tr,2)+((-

1)+2*rand(1))*Len2;%Xi=Xi+rand(-

1,1)*Len2

X(j_g_tr,1)=bound(X(j_g_tr,1),start1, end1);

X(j_g_tr,2)=bound(X(j_g_tr,2),start2, end2);

end;

end;

%信息素更新

subplot(2,2,2); %%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%% Plot 1

bar([X(BestIndex,1)

X(BestIndex,2)],0.25);

%colormap (cool);

axis([0 3 -40 40 ]) ;

title ({date;['Iteration ',

num2str(Echo)]});

xlabel(['Min_x =

',num2str(X(BestIndex,1)),' ',

'Min_y = ', num2str(X(BestIndex,2))]);

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