多目标樽海鞘算法MATLAB实战

%%主程序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);iter=0;
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
    display(['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');
set(gcf, 'pos', [403   466   230   200])