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Grouping Genetic Algorithm for the Blockmodel Problem
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AI
DOI：10.1109/TEVC.2009.2023793.png)
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Abstract
En 中文
Many areas of research examine the relationships between objects. A subset of these research areas focuses on methods for creating groups whose members are similar based on some specific attribute(s). The blockmodel problem has as its objective to group objects in order to obtain a small number of large groups of similar nodes. In this paper, a grouping genetic algorithm (GGA) is applied to the blockmodel problem. Testing on numerous examples from the literature indicates a GGA is an appropriate tool for solving this type of problem. Specifically, our GGA provides good solutions, even to large-size problems, in reasonable computational time.
Keywords:
Blockmodel
grouping genetic algorithm (GGA)
social network analysis
Journal
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1.8K
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