leaders.m
provides a Matlab implementation of algorithms that quantify suboptimality of
solutions to two combinatorial network optimization problems. For undirected
consensus networks, these problems arise in assignment of a pre-specified
number of nodes, as leaders, in order to minimize the mean-square deviation
from consensus.
We develop efficient algorithms that quantify performance bounds on
the global optimal values. Specifically, we obtain lower bounds by solving
the corresponding convex relaxations and we obtain upper bounds using a simple but
efficient greedy algorithm.
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