Parameter Identification of a Soil Constitutive Model Based on a Hybrid Genetic Differential Evolution Algorithm

Aiming to address the problem of selecting the parameters of a soil constitutive model in the calculation of foundation pit stability, this paper proposes a hybrid genetic differential evolution algorithm (GADE) which performs by “jumping out of local optima” with “fast convergence” based on the hybrid optimization algorithm strategy and compares the advantages and disadvantages of genetic algorithms (GAs) and differential evolution algorithms (DEs). Three typical test functions were used to evaluate the search efficiency and convergence speed of GAs, DEs, and GADE, respectively. It was found that GADE has the fastest convergence speed and can search for the global optimal solution to the problem, which highlights its excellent optimization performance. At the same time, taking the Shimao Binjiang deep foundation pit as an example, GADE was used to invert the soil modulus parameters of a CX1 measuring point and construct a finite-element model for calculation. The results showed that the simulated calculation curve and the measured displacement curve were in good agreement and the curve fitting reached 95.05%, indicating the applicability and feasibility of applying GADE to identify soil parameters.

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