Analysis of Search Heuristics for Improving the Resistance of Complex Networks to Epidemic Processes

Fernando Concatto, Alex Luciano Roesler Rese, Rafael de Santiago


The uninhibited propagation of an infectious agent through a network
can cause extensive damage of various types on the economy and public health
for instance. Therefore, this study sought to develop a strategy to make complex
networks more resistant to these agents through modifications in the topology
of the network. For this purpose, we employed the epidemic threshold theory,
which dictates that the epidemic resistance of a network is inversely proportional
to the spectral radius of its adjacency matrix. Thus, we developed a local
search to minimize the spectral radius through the removal of links, applying
it to a set of real networks, seeking to identify the increase in resistance as a
function of the number of links removed.

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