Genetic Algorithms for the Calibration of Constitutive Models for Soils

This paper presents a study that uses an innovative numerical method called the “genetic algorithm” for material parameter optimization in constitutive modeling. The paper introduces a new scheme, a fitness function, to estimate the error of predicted behavior due to a given set of material parameters. Optimization efficiency of the proposed fitness function is analyzed by changing the selected genetic algorithm parameters. The genetic algorithm and the new fitness function were found to be capable of optimizing material parameters of complex constitutive models.

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