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Optimal disintegration strategy in spatial networks with disintegration circle model.

Ye Deng1, Jun Wu2, Mingze Qi1

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This study introduces an optimization model for spatial network disintegration, using tabu search to find optimal strategies. The best approach targets nodes near the average degree for maximum impact, aiding network protection.

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Area of Science:

  • Network science
  • Graph theory
  • Spatial analysis

Background:

  • Network disintegration is crucial for applications like epidemic control and disrupting illicit networks.
  • Existing methods often overlook the spatial embedding of networks, limiting effectiveness.

Purpose of the Study:

  • To develop an optimal disintegration strategy for spatial networks.
  • To incorporate spatial information into network disintegration models.
  • To identify key network vulnerabilities through disintegration analysis.

Main Methods:

  • Developed an optimization model for spatial network disintegration using multiple disintegration circles.
  • Employed a tabu search algorithm to find the optimal disintegration strategy.
  • Analyzed the impact of spatial node distribution on disintegration effectiveness.

Main Results:

  • A global search successfully identified the optimal disintegration strategy in spatial networks.
  • The most effective strategy involves placing disintegration circles to cover nodes near the average degree.
  • This strategy maximizes the destructive effect on the network.

Conclusions:

  • Spatial information is critical for effective network disintegration strategies.
  • Targeting nodes with average degree centrality is an efficient method for network disruption.
  • Findings offer insights for network protection by identifying critical vulnerabilities.