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Reducing convergence times of self-propelled swarms via modified nearest neighbor rules

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  • George, Mishel
  • Ghose, Debasish

Abstract

Vicsek et al. proposed a biologically inspired model of self-propelled particles, which is now commonly referred to as the Vicsek model. Recently, attention has been directed at modifying the Vicsek model so as to improve convergence properties. In this paper, we propose two modification of the Vicsek model which leads to significant improvements in convergence times. The modifications involve an additional term in the heading update rule which depends only on the current or the past states of the particle’s neighbors. The variation in convergence properties as the parameters of these modified versions are changed are closely investigated. It is found that in both cases, there exists an optimal value of the parameter which reduces convergence times significantly and the system undergoes a phase transition as the value of the parameter is increased beyond this optimal value.

Suggested Citation

  • George, Mishel & Ghose, Debasish, 2012. "Reducing convergence times of self-propelled swarms via modified nearest neighbor rules," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(16), pages 4121-4127.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:16:p:4121-4127
    DOI: 10.1016/j.physa.2012.03.028
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    Cited by:

    1. Li, Qing & Zhang, Lingwei & Jia, Yongnan & Lu, Tianzhao & Chen, Xiaojie, 2022. "Modeling, analysis, and optimization of three-dimensional restricted visual field metric-free swarms," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    2. Chen, Yu-Rong & Zhang, Xian-Xia & Yu, Yin-Sheng & Ma, Shi-Wei & Yang, Banghua, 2022. "Enhancing convergence efficiency of self-propelled agents using direction preference," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).

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