Critical node detection problem for complex network in undirected weighted networks

Wei Chen, Manrui Jiang, Cheng Jiang and Jun Zhang

Physica A: Statistical Mechanics and its Applications, 2020, vol. 538, issue C

Abstract: Detection of critical nodes in complex networks has recently received extensive attention. Currently, studies of the critical nodes problem (CNP) mainly focus on two problem types: “critical nodes problem/positive” (CNP-Pos) and “critical nodes problem/negative” (CNP-Neg). However, to the best of our knowledge, few studies have been conducted on CNP-Neg for weighed networks. In this paper, we investigate CNP-Neg in undirected weighted networks. We first propose a novel metric DFW to evaluate network fragmentation. Then, we formulate a new nonconvex mixed-integer quadratic programming model, named MIQPM, that aims to simultaneously minimize pairwise connectivity and maximize the weights between the nodes. After that, a general greedy algorithm is employed to solve the corresponding optimization problem. Finally, comparison experiments are carried out for several synthetic networks and four real-world networks to demonstrate the effectiveness of the proposed approaches.

Keywords: Critical nodes problem; Weighted network; Network fragmentation; Mixed-integer quadratic programming; Greedy algorithm (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:538:y:2020:i:c:s0378437119316279

DOI: 10.1016/j.physa.2019.122862

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