A Systematic Research on System Recovery Based on Improved Genetic Algorithm and Quotient Resilience Model Under Attack and Damage

Author:

Zhen Li,Lu Tian,Xu Sun Chen,Mei Wu YuORCID,Sheng Wang Dong,Hong Miao

Abstract

AbstractThe vulnerability of the current network has become an urgent problem to be solved. The focus of network protection should be shifted from traditional network protection to the direction of effective recovery even after being attacked and damaged, and then, the concept of resilience came into being. This paper selects physical explosion attacks to establish damaged network. An improved system resilience recovery strategy is established which considers task importance and time efficiency. Aiming at the initial population is too random, easy to mature and with poor solution, this paper improves genetic algorithm by new greedy model in population initialization and head-to-head mutation operator. Simulation shows that the improved genetic algorithm is better and more stable, the improved quotient model is more effective in system resilience recovery measured by index-E proposed in this paper.

Funder

National Outstanding Youth Science Fund Project of National Natural Science Foundation of China

Jiangsu University of Science and Technology, Reliability and System Engineering Open Group (JRSOG) Open Fund

Publisher

Springer Science and Business Media LLC

Subject

Computational Mathematics,General Computer Science

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Design and Optimization of Digital Substation Integrated Automation System Based on Improved Genetic Algorithm;2023 International Conference on Power, Electrical Engineering, Electronics and Control (PEEEC);2023-09-25

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