Pareto Front
by
Yi Cao
31 Oct 2007
(Updated
29 Jul 2008)
Two efficient algorithms to find Pareto Front

front=paretoGroup(X)

function front=paretoGroup(X)
% PARETOGROUP To get the Pareto Front from a given set of points.
% synopsis: front =paretoGroup (objectiveMatrix)
% where:
% objectiveMatrix: [number of points X number of objectives] array
% front: [number of points X 1] logical vector to indicate if ith
% point belongs to the Pareto Front (true) or not (false).
%
% by Yi Cao, Cranfield University, 31 June 2007
%
% Identify the Pareto Front from a set of points in objective space is the
% most important and also the most timeconsuming task in multiobjective
% optimization. This code splits the given objective set into several
% smaller groups to be examined by the efficient paretofront algorithm.
% Then, the Pareto Fronts of each group are combined as one set to be
% checked by the paretofront algorithm to determine the overall Pareto
% Front. In this way, the overal computation time can be reduced about
% half.
%
% Example:
% X = rand(1000000,4);
% t0 = cputime;
% Y1=paretoGroup(X); %mex implementation without sorting.
% t1=cputime  t0;
% t0 = cputime;
% Y2=paretofront(X);
% t2=cputime  t0;
% isequal(Y1,Y2) %shoudl be 1
% disp([t1 t2])
% Computation time based on Intel(R) Core(TM)2 CPU T2500 @ 2.0GHz, 2.0 GB of RAM
% 0.6844 1.4404
%
[m,n]=size(X);
groupcut=floor(2^13/n);
gRoup=max(1,ceil(m/groupcut));
front=false(m,1);
for k=1:gRoup
z0=(k1)*groupcut;
z=(z0+1):min(z0+groupcut,m);
front(z)=paretofront(X(z,:));
end
if gRoup>1
front(front)=paretofront(X(front,:));
end


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