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A variable neighborhood search method for a two-mode blockmodeling problem in social network analysis

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  • BRUSCO, MICHAEL
  • DOREIAN, PATRICK
  • LLOYD, PAULETTE
  • STEINLEY, DOUGLAS

Abstract

This paper presents a variable neighborhood search (VNS) algorithm that is specially designed for the blockmodeling of two-mode binary network matrices in accordance with structural equivalence. Computational results for 768 synthetic test networks revealed that the VNS heuristic outperformed a relocation heuristic (RH) and a tabu search (TS) method for the same problem. Next, the three heuristics were applied to two-mode network data pertaining to the votes of member countries on resolutions in the United Nations General Assembly. A comparative analysis revealed that the VNS heuristic often provided slightly better criterion function values than RH and TS, and that these small differences in criterion function values could sometimes be associated with substantial differences in the actual partitions obtained. Overall, the results suggest that the VNS heuristic is a promising approach for blockmodeling of two-mode binary networks. Recommendations for extensions to stochastic blockmodeling applications are provided.

Suggested Citation

  • Brusco, Michael & Doreian, Patrick & Lloyd, Paulette & Steinley, Douglas, 2013. "A variable neighborhood search method for a two-mode blockmodeling problem in social network analysis," Network Science, Cambridge University Press, vol. 1(2), pages 191-212, August.
    • Handle: RePEc:cup:netsci:v:1:y:2013:i:02:p:191-212_00
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    Cited by:

    1. Stolze, Hannah J. & Brusco, Michael J. & Smith, Jeffery S., 2021. "Exploring the social mechanisms for variation reduction for direct store delivery (DSD) and vendor managed inventory performance: An integrated network governance and coordination theory perspective," International Journal of Production Economics, Elsevier, vol. 234(C).

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