Open AccessResearch on resilience recovery strategy optimization of highway network after disaster based on genetic algorithm
Author(s) -
Fayu Zhao
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2083/3/032014
Subject(s) - resilience (materials science) , computer science , task (project management) , genetic algorithm , process (computing) , traffic network , reliability engineering , mathematical optimization , operations research , transport engineering , engineering , mathematics , systems engineering , materials science , machine learning , composite material , operating system
In order to effectively improve the recovery efficiency of the highway network after the disaster and make the road network quickly recover to the normal operation level, the recovery strategy of the highway network after the disaster aiming at the optimal toughness was studied and formulated. First clear the toughness in this paper the definition and put forward the two toughness indexes, then constructs the model of road network resilience restored after a disaster, in considering the time, money, resources and cost conditions, through the corresponding genetic algorithm to solve, it is concluded that the shortest road repair, restore minimum loss in the process of recovery program. Finally, an example is given to illustrate how to use the model established in this paper. The results show that from the beginning of repair to the end of repair, the repair team can achieve the expected task in a faster time, which minimizes the performance loss of the road network and saves the cost.