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A novel mixed integer linear programming model for clustering relational networks. (English) Zbl 1384.90065
Summary: Integer programming models for clustering have applications in diverse fields addressing many problems such as market segmentation and location of facilities. Integer programming models are flexible in expressing objectives subject to some special constraints of the clustering problem. They are also important for guiding clustering algorithms that are capable of handling high-dimensional data. Here, we present a novel mixed integer linear programming model especially for clustering relational networks, which have important applications in social sciences and bioinformatics. Our model is applied to several social network data sets to demonstrate its ability to detect natural network structures.
MSC:
 90C11 Mixed integer programming 90C27 Combinatorial optimization 90C35 Programming involving graphs or networks 90C90 Applications of mathematical programming 91D30 Social networks; opinion dynamics 05C82 Small world graphs, complex networks (graph-theoretic aspects) 05C12 Distance in graphs 68R05 Combinatorics in computer science 68R10 Graph theory (including graph drawing) in computer science 90C05 Linear programming
Software:
clValid; cluster (R); igraph; Silhouettes; R; CPLEX
Full Text:
References:
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