智能优化算法源代码

1 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 2 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(BestI...