A Hybrid Metaheuristic for the Maximum k-Plex Problem

被引：7
|
作者：
Gujjula, Krishna Reddy [1 ]
Seshadrinathan, Krishnan Ayalur [1 ]
Meisami, Amirhossein [1 ]
机构：
[1] Texas A&M Univ, Dept Ind & Syst Engn, 3131 TAMU, College Stn, TX 77843 USA
来源：
EXAMINING ROBUSTNESS AND VULNERABILITY OF NETWORKED SYSTEMS | 2014年 / 37卷
关键词：
social network analysis; clique relaxations; k-plex; CLIQUE RELAXATION MODELS;
D O I：
10.3233/978-1-61499-391-9-83
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Social network analysis is an area of research that is gathering interest and importance since the turn of the century, especially with increased technology proliferation. Graph theory is predominantly being used in the analysis of social networks. The maximum k-plex problem. which belongs to the category of clique relaxation problems has been studied by researchers in this field. This problem is known to be NP-hard. This paper proposes an amalgamation of a greedy randomized adaptive search procedure and tabu search metaheuristic to solve the problem. The performance of the proposed hybrid metaheuristic is tested on well-known instances of graphs and the computational results are reported.
引用
收藏
页码：83 / 92
页数：10
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