Study of Structural Damage Detection with Multi-objective Function Genetic Algorithms

Genetic algorithms applied to structural damage detection have broad application prospects. Based on the traditional genetic algorithms, this paper conducts the improvement research of the objective function with the incorporation of multi-objective function optimization. On the basis of three typical structural damage scenarios, we took a comprehensive study using different multi-objective function of the genetic algorithm from the standpoint of both convergence speed and accuracy. Data analysis obtained the corresponding optimal portfolio of weight coefficient in three typical scenarios, further fitted a universal formula for the weight coefficient value choice (WCCF). And an example to demonstrate the reliability of the formula is provided, which is supposed to provide more reference for quadratic optimization based on preliminary analysis for practical application.