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<p>This study presents a comprehensive analysis of weighted bipartite networks, investigating their sensitivity to random weight variations, identifying critical links/nodes through zeroing-out experiments, and proposing multi-objective optimization models for network enhancement. By systematically examining the effects of random weight variations on three bipartite indexes (nestedness, modularity, and robustness), we assess the stability and resilience of the network under stochastic perturbations. Through targeted experiments, we identify critical links/nodes that significantly influence network topology and functionality. Lastly, we propose tri-objective optimization models that integrate objectives to guide network design and management decisions. Our findings provide valuable insights into the dynamics and optimization of weighted bipartite networks, with implications for network resilience, efficiency, and performance optimization. An example related to the Athens metro system illustrates the proposed approach.</p>

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Sensitivity, criticality, and optimization in bipartite networks: application in urban transit infrastructure

  • 期刊论文

  • 发表日期：

    2025年3月28日

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  • Claudio M. Rocco,
  • Kash Barker,
  • Sridhar Radhakrishnan,
  • Jose Moronta

摘要

This study presents a comprehensive analysis of weighted bipartite networks, investigating their sensitivity to random weight variations, identifying critical links/nodes through zeroing-out experiments, and proposing multi-objective optimization models for network enhancement. By systematically examining the effects of random weight variations on three bipartite indexes (nestedness, modularity, and robustness), we assess the stability and resilience of the network under stochastic perturbations. Through targeted experiments, we identify critical links/nodes that significantly influence network topology and functionality. Lastly, we propose tri-objective optimization models that integrate objectives to guide network design and management decisions. Our findings provide valuable insights into the dynamics and optimization of weighted bipartite networks, with implications for network resilience, efficiency, and performance optimization. An example related to the Athens metro system illustrates the proposed approach.