Clique Relaxation Models in Social Network Analysis

Jeffrey Pattillo (), Nataly Youssef () and Sergiy Butenko ()
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Jeffrey Pattillo: Texas A&M University
Nataly Youssef: Texas A&M University
Sergiy Butenko: Texas A&M University

Chapter Chapter 5 in Handbook of Optimization in Complex Networks, 2012, pp 143-162 from Springer

Abstract: Abstract Clique relaxation models that were originally introduced in the literature on social network analysis are not only gaining increasing popularity in a wide spectrum of complex network applications, but also keep garnering attention of mathematicians, computer scientists, and operations researchers as a promising avenue for fruitful theoretical investigations. This chapter describes the origins of clique relaxation concepts and provides a brief overview of mathematical programming formulations for the corresponding optimization problems, algorithms proposed to solve these problems, and selected real-life applications of the models of interest.

Keywords: Social Network Analysis; Maximum Clique; Greedy Randomize Adaptive Search Procedure; Edge Density; Greedy Heuristic (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1007/978-1-4614-0857-4_5

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