A 2D lattice
Matlab code
lattice_publish
n = 81;
N = sqrt(n);
ne = 0.5*( 2*4 + (N-2)*3*4 + (N-2)^2*4 );
idx = zeros(2,ne);
for i = 1:N
idx(1,(N-1)*(i-1)+1:(N-1)*i) = N*(i-1)+1:N*(i-1)+(N-1);
idx(2,(N-1)*(i-1)+1:(N-1)*i) = N*(i-1)+2:N*(i-1)+N;
end
for i = 1:N
idx(1,ne/2+ ((N-1)*(i-1)+1:(N-1)*i) ) = i:N:(i+(N-2)*N);
idx(2,ne/2+ ((N-1)*(i-1)+1:(N-1)*i) ) = (i:N:(i+(N-2)*N))+N;
end
Eg = incmat(idx);
L = Eg*Eg';
kappa = diag(L);
kval = 1:1:40;
Jlow = zeros(size(kval));
Jup = zeros(size(kval));
LSgreed = zeros(n,length(kval));
for i = 1:length(kval)
Nl = kval(i);
flag = 1;
[Jlow(i),Jup(i),LSgreed(:,i)] = leaders(L,Nl,kappa,flag);
end
Computational results
Performance bounds
Bounds on the global optimal value of the noise-corrupted leader selection problem
for the 2D lattice example.
Selection of leaders
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Selection of noise-corrupted leaders ( ) obtained using
greedy algorithm (i.e., one-leader-at-a-time algorithm followed by the swap procedure)
for the 2D lattice example.
For , the center node provides the optimal
selection of a single leader. As increases, nodes away from the center
node are selected; for example, for , nodes , are
selected and for , nodes , , are selected.
Selection of nodes farther away from the center becomes more significant for
and .
The selection of leaders exhibits symmetry with respect to the center
of the lattice. For example, in Fig. (b), the leaders at , denoted by
( ) provide the same objective function as leaders denoted by ( ). Similarly,
in Fig. (c), the four selections of three leaders denoted by ( ), ( ),
( ), and ( ) all provide the same performance .
Also note that when is large, almost uniform spacing between leaders is
observed; see Fig. (f). This is in contrast to the random network example where boundary nodes were selected when the number
of leaders is large.
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