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.
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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