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A Tabu-Search Heuristic for Deterministic Two-Mode Blockmodeling of Binary Network Matrices

Published online by Cambridge University Press:  01 January 2025

Michael Brusco  and
Douglas Steinley
Michael Brusco*
Affiliation:
Florida State University
Douglas Steinley
Affiliation:
University of Missouri-Columbia
*
Requests for reprints should be sent to Michael Brusco, Department of Marketing, College of Business, Florida State University, Tallahassee, FL 32306-1110, USA. E-mail: mbrusco@fsu.edu
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Abstract

Two-mode binary data matrices arise in a variety of social network contexts, such as the attendance or non-attendance of individuals at events, the participation or lack of participation of groups in projects, and the votes of judges on cases. A popular method for analyzing such data is two-mode blockmodeling based on structural equivalence, where the goal is to identify partitions for the row and column objects such that the clusters of the row and column objects form blocks that are either complete (all 1s) or null (all 0s) to the greatest extent possible. Multiple restarts of an object relocation heuristic that seeks to minimize the number of inconsistencies (i.e., 1s in null blocks and 0s in complete blocks) with ideal block structure is the predominant approach for tackling this problem. As an alternative, we propose a fast and effective implementation of tabu search. Computational comparisons across a set of 48 large network matrices revealed that the new tabu-search heuristic always provided objective function values that were better than those of the relocation heuristic when the two methods were constrained to the same amount of computation time.

Keywords

clusteringtwo-mode networksblockmodelingtabu searchheuristics
Type
Original Paper
Information
Psychometrika , Volume 76 , Issue 4 , October 2011 , pp. 612 - 633
Copyright
Copyright © 2011 The Psychometric Society

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