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IEEE Access | Vol.8, Issue. | 2020-01-01 | Pages

IEEE Access

Controllability Robustness Against Cascading Failure for Complex Logistic Network Based on Dynamic Cascading Failure Model

Wang, Shaohua   Yang, Yue   Li, Xiaoni   Sun, Liyue   Guo, Konghui   Li, Yongxing  
Abstract

Inspired by the empirical dynamic characteristics of the load of real logistics network, we propose a dynamic cascading failure model against cascading failure, which is more suitable for complex logistics network by adding dynamic factors based on the nonlinear load-capacity model under initial residual capacity load-redistribution strategy. The simulation is executed on the complex logistics network model and the results show that the controllability robustness and economy after cascading failure based on the dynamic cascading failure model is feasible and effective. It can effectively reduce the logistics cost and enhance controllability robustness against cascading failure by adjusting the network cost $e$ and capacity parameter $\gamma $ , so as to balance the controllability robustness and economy for the complex logistics network.

Original Text (This is the original text for your reference.)

Controllability Robustness Against Cascading Failure for Complex Logistic Network Based on Dynamic Cascading Failure Model

Inspired by the empirical dynamic characteristics of the load of real logistics network, we propose a dynamic cascading failure model against cascading failure, which is more suitable for complex logistics network by adding dynamic factors based on the nonlinear load-capacity model under initial residual capacity load-redistribution strategy. The simulation is executed on the complex logistics network model and the results show that the controllability robustness and economy after cascading failure based on the dynamic cascading failure model is feasible and effective. It can effectively reduce the logistics cost and enhance controllability robustness against cascading failure by adjusting the network cost $e$ and capacity parameter $\gamma $ , so as to balance the controllability robustness and economy for the complex logistics network.

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Wang, Shaohua, Yang, Yue, Li, Xiaoni, Sun, Liyue, Guo, Konghui, Li, Yongxing,.Controllability Robustness Against Cascading Failure for Complex Logistic Network Based on Dynamic Cascading Failure Model. 8 (),.

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