A simulated annealing heuristic for maximum correlation core/periphery partitioning of binary networks

Michael Brusco, Hannah J Stolze, Michaela Hoffman and Douglas Steinley

PLOS ONE, 2017, vol. 12, issue 5, 1-17

Abstract: A popular objective criterion for partitioning a set of actors into core and periphery subsets is the maximization of the correlation between an ideal and observed structure associated with intra-core and intra-periphery ties. The resulting optimization problem has commonly been tackled using heuristic procedures such as relocation algorithms, genetic algorithms, and simulated annealing. In this paper, we present a computationally efficient simulated annealing algorithm for maximum correlation core/periphery partitioning of binary networks. The algorithm is evaluated using simulated networks consisting of up to 2000 actors and spanning a variety of densities for the intra-core, intra-periphery, and inter-core-periphery components of the network. Core/periphery analyses of problem solving, trust, and information sharing networks for the frontline employees and managers of a consumer packaged goods manufacturer are provided to illustrate the use of the model.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0170448

DOI: 10.1371/journal.pone.0170448

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