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A heuristic approach for the distance-based critical node detection problem in complex networks

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  • Glory Uche Alozie
  • Ashwin Arulselvan
  • Kerem Akartunalı
  • Eduardo L. Pasiliao

Abstract

The distance-based critical node problem involves identifying a subset of nodes in a network whose removal minimises a pre-defined distance-based connectivity measure. Having the classical critical node problem as a special case, the distance-based critical node problem is computationally challenging. In this article, we study the distance-based critical node problem from a heuristic algorithm perspective. We consider the distance-based connectivity objective whose goal is to minimise the number of node pairs connected by a path of length at most k, subject to budgetary constraints. We propose a centrality based heuristic which combines a backbone-based crossover procedure to generate good offspring solutions and a centrality-based neighbourhood search to improve the solution. Extensive computational experiments on real-world and synthetic graphs show the effectiveness of the developed heuristic in generating good solutions when compared to exact solution. Our empirical results also provide useful insights for future algorithm development.

Suggested Citation

  • Glory Uche Alozie & Ashwin Arulselvan & Kerem Akartunalı & Eduardo L. Pasiliao, 2022. "A heuristic approach for the distance-based critical node detection problem in complex networks," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 73(6), pages 1347-1361, June.
  • Handle: RePEc:taf:tjorxx:v:73:y:2022:i:6:p:1347-1361
    DOI: 10.1080/01605682.2021.1913078
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    Cited by:

    1. Zhou, Yangming & Wang, Gezi & Hao, Jin-Kao & Geng, Na & Jiang, Zhibin, 2023. "A fast tri-individual memetic search approach for the distance-based critical node problem," European Journal of Operational Research, Elsevier, vol. 308(2), pages 540-554.

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