Network Resilience Recovery Method Based on Improved Genetic Algorithm
CUI Xiaosong
PAN Chengsheng
Abstract：Aiming at the problems such as excessive randomness of initial population and low efficiency of evolutionary opera-tor existing in the field of network resilience recovery path planning of basic genetic algorithm,an improved genetic algorithm based network resilience recovery method is proposed.Firstly,quotient model is used to measure resilience,and task importance is used to model network resilience.Secondly,time and spare parts constraints and parallel group maintenance mechanisms are included in the study of resilience,and the initial population generation and mutation operator of genetic algorithm are improved.Finally,the improved genetic algorithm is used to solve the maximum task importance of network resilience recovery within a specified time,and the optimal solution of the model is obtained.In the simulation example,the comparison shows that the system using this algorithm has higher resilience recovery ability,which proves the effectiveness of the model and algorithm.
Keywords：resiliencetask importancespare partsgenetic algorithmrecovery strategy
Publication Date：2024-09-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 2549-2554 )