Extremal Optimization and Network Community Structure
نویسندگان
چکیده
The network community structure detection problem has been recently approached with several variants of an extremal optimization algorithm. An extremal optimization algorithm is a stochastic local search method that evolves pairs of individuals that can be represented as having several components by randomly replacing components having worst fitnesses. The number of components to be replaced in one iteration influences both the exploitation and exploration capabilities of the method; an efficient method of adjusting this number during the search may significantly influence the quality of results. In this paper we explore the use of several updating mechanisms for this number. Numerical experiments are used evaluate them and also to compare results obtained with those provided by other state-of-art methods.
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