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Revisiting epidemic network evolution with a new representation

This study revisits the test problem of evolving a network that gives the contact structure of a population so as to maximize the length of epidemics based on the network. A novel feature of the study is to use a new representation for network evolution. The representation consists of a sequence of editing commands that modify a starting network to specify a final network evaluated for its epidemic properties. The representation is parametrized by specifying the probability each editing command will be generated in initial populations and during mutation. The original work on long-epidemic networks required a sophisticated type of evolutionary algorithm, the restarting-recentering evolutionary algorithm, to obtain high-fitness results. Use of the new representation permits superior results and obtains them using a simpler type of evolutionary algorithm. A second novel result is the introduction of a new type of tournament selection, useful for at least some types of evolution that use stochastic fitness functions.