多目标樽海鞘群算法matlab代码.zip

clc clear close all % Change these details with respect to your problem ObjectiveFunction=@ZDT1; dim=5; lb=0; ub=1; obj_no=2; if size(ub,2)==1 ub=ones(1,dim)*ub; lb=ones(1,dim)*lb; end max_iter=100; N=200; ArchiveMaxSize=100; Archive_X=zeros(100,dim); Archive_F=ones(100,obj_no)*inf; Archive_member_no=0; r=(ub-lb)/2; V_max=(ub(1)-lb(1))/10; Food_fitness=inf*ones(1,obj_no); Food_position=zeros(dim,1); Salps_X=initialization(N,dim,ub,lb); fitness=zeros(N,2); V=initialization(N,dim,ub,lb); position_history=zeros(N,max_iter,dim); for iter=1:max_iter c1 = 2*exp(-(4*iter/max_iter)^2); % Eq. (3.2) in the paper for i=1:N %Calculate all the objective values first Salps_fitness(i,:)=ObjectiveFunction(Salps_X(:,i)'); if dominates(Salps_fitness(i,:),Food_fitness) Food_fitness=Salps_fitness(i,:); Food_position=Salps_X(:,i); end end [Archive_X, Archive_F, Archive_member_no]=UpdateArchive(Archive_X, Archive_F, Salps_X, Salps_fitness, Archive_member_no); if Archive_member_no>ArchiveMaxSize Archive_mem_ranks=RankingProcess(Archive_F, ArchiveMaxSize, obj_no); [Archive_X, Archive_F, Archive_mem_ranks, Archive_member_no]=HandleFullArchive(Archive_X, Archive_F, Archive_member_no, Archive_mem_ranks, ArchiveMaxSize); else Archive_mem_ranks=RankingProcess(Archive_F, ArchiveMaxSize, obj_no); end Archive_mem_ranks=RankingProcess(Archive_F, ArchiveMaxSize, obj_no); % Archive_mem_ranks % Chose the archive member in the least population area as food` % to improve coverage index=RouletteWheelSelection(1./Archive_mem_ranks); if index==-1 index=1; end Food_fitness=Archive_F(index,:); Food_position=Archive_X(index,:)'; for i=1:N index=0; neighbours_no=0; if i<=N/2 for j=1:1:dim c2=rand(); c3=rand(); % Eq. (3.1) in the paper if c3<0.5 Salps_X(j,i)=Food_position(j)+c1*((ub(j)-lb(j))*c2+lb(j)); else Salps_X(j,i)=Food_position(j)-c1*((ub(j)-lb(j))*c2+lb(j)); end end elseif i>N/2 && i<N+1 point1=Salps_X(:,i-1); point2=Salps_X(:,i); Salps_X(:,i)=(point2+point1)/(2); % Eq. (3.4) in the paper end Flag4ub=Salps_X(:,i)>ub'; Flag4lb=Salps_X(:,i)<lb'; Salps_X(:,i)=(Salps_X(:,i).*(~(Flag4ub+Flag4lb)))+ub'.*Flag4ub+lb'.*Flag4lb; end disp(['At the iteration ', num2str(iter), ' there are ', num2str(Archive_member_no), ' non-dominated solutions in the archive']); end figure Draw_ZDT1(); hold on plot(Archive_F(:,1),Archive_F(:,2),'ro','MarkerSize',8,'markerfacecolor','k'); legend('True PF','Obtained PF'); title('MSSA');