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Efficient disintegration strategy in directed networks based on tabu search

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  • Yu, Yang
  • Deng, Ye
  • Tan, Suo-Yi
  • Wu, Jun

Abstract

The problem of network disintegration, which aims at identifying the critical nodes or edges whose removal will lead to a network collapse, has attracted much attention due to its wide applications. This paper focuses on the disintegration of directed networks. We propose a disintegration strategy based on tabu search. Experiments show that the disintegration effect of our strategy is obviously better than those of typical disintegration strategies based on local structural properties. Moreover, we find that the critical nodes identified to remove in directed networks are not those nodes with large degree or betweenness centrality that always are the crucial properties in undirected network.

Suggested Citation

  • Yu, Yang & Deng, Ye & Tan, Suo-Yi & Wu, Jun, 2018. "Efficient disintegration strategy in directed networks based on tabu search," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 435-442.
    • Handle: RePEc:eee:phsmap:v:507:y:2018:i:c:p:435-442
    DOI: 10.1016/j.physa.2018.05.079
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    References listed on IDEAS

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    Cited by:

    1. Chen, Wenhao & Li, Jichao & Jiang, Jiang & Chen, Gang, 2022. "Weighted interdependent network disintegration strategy based on Q-learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).

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