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

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  • Michael Brusco
  • Hannah J Stolze
  • Michaela Hoffman
  • Douglas Steinley

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.

Suggested Citation

  • Michael Brusco & Hannah J Stolze & Michaela Hoffman & Douglas Steinley, 2017. "A simulated annealing heuristic for maximum correlation core/periphery partitioning of binary networks," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-17, May.
    • Handle: RePEc:plo:pone00:0170448
    DOI: 10.1371/journal.pone.0170448
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    References listed on IDEAS

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    1. Patrick Groenen & Willem Heiser, 1996. "The tunneling method for global optimization in multidimensional scaling," Psychometrika, Springer;The Psychometric Society, vol. 61(3), pages 529-550, September.
    2. Brusco, Michael J., 2014. "A comparison of simulated annealing algorithms for variable selection in principal component analysis and discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 38-53.
    3. L. Ark & Marcel Croon & Klaas Sijtsma, 2008. "Mokken Scale Analysis for Dichotomous Items Using Marginal Models," Psychometrika, Springer;The Psychometric Society, vol. 73(2), pages 183-208, June.
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