如果可以，求一个外加租赁条件的蚁群算法matlab程序最好有注释

飞翔の板砖

如题。。。蚁群太难，自己实在不会编

mingtingqing

clear;loc = [0.3663, 0.9076; 0.7459, 0.8713; 0.4521, 0.8465;0.7624, 0.7459; 0.7096, 0.7228; 0.0710, 0.7426;0.4224, 0.7129; 0.5908, 0.6931; 0.3201, 0.6403;0.5974, 0.6436; 0.3630, 0.5908; 0.6700, 0.5908;0.6172, 0.5495; 0.6667, 0.5446; 0.1980, 0.4686;0.3498, 0.4488; 0.2673, 0.4274; 0.9439, 0.4208;0.8218, 0.3795; 0.3729, 0.2690; 0.6073, 0.2640;0.4158, 0.2475; 0.5990, 0.2261; 0.3927, 0.1947;0.5347, 0.1898; 0.3960, 0.1320; 0.6287, 0.0842;0.5000, 0.0396; 0.9802, 0.0182; 0.6832, 0.8515];% loc=rand(50,2);NumCity=length(loc);for i = 1:NumCity,for j = 1:NumCity,distance(i, j) = norm(loc(i, - loc(j, );endenddistance=distance+eye(NumCity).*eps;%^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^%^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^%^^^^^^^^^^^^^^^^^^ Initialize AC Parameters ^^^^^^^^^^^^^% P: ant α β ρ η Q % V: 31 1 5 0.1 1./distance 100 ant=31; a=1; b=5; p=0.1; E=1./distance; Q=100;%^^^^^^^^^^^^t=ones(NumCity); Nm=200;Tabu=zeros(ant,NumCity); R_best=zeros(Nm,NumCity);L_ave=zeros(Nm,1); L_best=inf.*ones(Nm,1);%^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ticfor Nc=1:NmTabu=[];%^^^^^^^^^^^^^^^^^^ Put Ants into Cities ^^^^^^^^^^^^^ Randpos=[];for i=1ceil(ant/NumCity)),Randpos=[Randpos,randperm(NumCity)];endTabu(:,1)=(Randpos(1,1:ant))';%^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^%^^^^^^^^^^^^ Ants According To Probability Choose Next City ^^^^^^^^^^^^^for j=2:NumCity,for i=1:ant,VisitedCity=Tabu(i,1j-1));UnVisited=zeros(1,(NumCity-j+1))=UnVisited;Jc=1;for k=1:NumCityif length(find(VisitedCity==k))==0UnVisited(Jc)=k;Jc=Jc+1;endend %^^^^^^^^^^^^for k=1:length(UnVisited)P(k)=(t(VisitedCity(end),UnVisited(k)).^a)...*(E(VisitedCity(end),UnVisited(k)).^b);endP=P./sum(P);%^^^^^^^^^^^^Pcum=cumsum(P);Select=find(Pcum>=rand);% Select=find(P==max(P));ToVisit=UnVisited(Select(1));Tabu(i,j)=ToVisit;endendif Nc>=2,Tabu(1,=R_best(Nc-1,;end%^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^%^^^^^^^^^^^^ Record the Best Path ^^^^^^^^^^^^^ L=zeros(ant,1);dt=zeros(NumCity);for i=1:antR=Tabu(i,;for j=1NumCity-1), L(i)=L(i)+distance(R(j),R(j+1));endL(i)=L(i)+distance(R(1),R(NumCity));for j=1NumCity-1)dt(Tabu(i,j),Tabu(i,j+1))=dt(Tabu(i,j),Tabu(i,j+1))+Q./(L(i));enddt(Tabu(i,NumCity),Tabu(i,1))=dt(Tabu(i,NumCity),Tabu(i,1))+Q./L(i);endL_best(Nc)=min(L);pos=find(L==L_best(Nc));R_best(Nc,=Tabu(pos(1),;L_ave(Nc)=mean(L);t=(1-p).*t+dt;%^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^%^^^^^^^^^^^^ Updata the t ^^^^^^^^^^^^^% dt=zeros(NumCity);% for i=1:ant% for j=1:NumCity-1% dt(Tabu(i,j),Tabu(i,j+1))=dt(Tabu(i,j),Tabu(i,j+1))+Q./(L(i));% end% dt(Tabu(i,NumCity),Tabu(i,1))=dt(Tabu(i,NumCity),Tabu(i,1))+Q./L(i);% end% t=(1-p).*t+dt;% Tabu=zeros(ant,NumCity);endtocPos=find(L_best==min(L_best));Shortest_Route=R_best(Pos(1),;Shortest_Length=L_best(Pos(1));subplot(1,2,1)DrawRoute(loc,Shortest_Route)subplot(1,2,2)plot(L_best)hold onplot(L_ave)

千面之王

我也觉得蚁群好难