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Optimized inter-structure for enhancing the synchronizability of interdependent networks

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  • Yang, Yong
  • Tu, Lilan
  • Li, Kuanyang
  • Guo, Tianjiao

Abstract

In this paper, how to optimize the inter-structures to enhance the synchronizability of interdependent networks is investigated. Based on a genetic algorithm (GA), combined with two fitness functions, a new method is presented that optimizes inter-structures to enhance the synchronizability of interdependent networks. For bounded and unbounded synchronous regions, when the number of inter-connections or the inter-coupling strength related to the inter-structures is changed, we apply the proposed method to optimize the two interdependent networks. The first network, namely NW–BA network, includes a small-world subnet generated by Newman–Watts algorithm and a Barabá si–Albert scale-free subnet. The second network, ST–BA network, includes a star subnet and a BA subnet. Generally, the analyses and numerical simulation results demonstrate the proposed optimization method performs well. According to the betweenness correlation defined in this paper, as the number of inter-connections increase, the optimized inter-structures experience a process that shifts a nearly positive correlation to irrelevance. However, increasing the inter-coupling strength gradually makes no difference on optimized inter-structures. Overall, the results indicate that NW–BA networks are a better choice for interdependent networks than the ST–BA networks.

Suggested Citation

  • Yang, Yong & Tu, Lilan & Li, Kuanyang & Guo, Tianjiao, 2019. "Optimized inter-structure for enhancing the synchronizability of interdependent networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 310-318.
    • Handle: RePEc:eee:phsmap:v:521:y:2019:i:c:p:310-318
    DOI: 10.1016/j.physa.2019.01.082
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    References listed on IDEAS

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    Cited by:

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    2. Jiang, Jianhua & Yang, Xi & Meng, Xianqiu & Li, Keqin, 2020. "Enhance chaotic gravitational search algorithm (CGSA) by balance adjustment mechanism and sine randomness function for continuous optimization problems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    3. Jiang, Jianhua & Xu, Meirong & Meng, Xianqiu & Li, Keqin, 2020. "STSA: A sine Tree-Seed Algorithm for complex continuous optimization problems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).

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