.png){kind=icon}
返回
A derandomized approximation algorithm for the critical node detection problem
.png){kind=icon}
PRE
AI
DOI：10.1016/j.cor.2013.09.012.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper we propose an efficient approximation algorithm for determining solutions to the critical node detection problem (CNDP) on unweighted and undirected graphs. Given a user-defined number of vertices k > 0, the problem is to determine which k nodes to remove such as to minimize pairwise connectivity in the induced subgraph. We present a simple, yet powerful, algorithm that is derived from a randomized rounding of the relaxed linear programming solution to the CNDP. We prove that the expected solution quality obtained by the linear-time algorithm is bounded by a constant. To highlight the algorithm quality four common complex network models are utilized, in addition to four real-world networks. (C) 2013 Elsevier Ltd. All rights reserved.
Keyword:
Critical node detection problem
Randomized rounding
Complex network
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
C
IF:
4.3
论文数:
6.5K
被引数:
1.8W
机构
引用论文
.png){kind=icon}
Electrostatic Free Energy and Other Properties of States Having Nonequilibrium Polarization. I具有非平衡极化状态的静电自由能和其他性质。我
OAAI
OAAI分享收藏分享收藏
查看更多内容