In geotechnical engineering, based on the theory of inverse analysis of displacement, the
problem for identification of material parameters can be transformed into an optimization problem.
Commonly, because of the non-linear relationship between the identified parameters and the
displacement, the objective function bears the multimodal characteristic in the variable space. So to
solve better the multimodal characteristic in the non-linear inverse analysis, a new global
optimization algorithm, which integrates the dynamic descent algorithm and the modified BFGS
(Brogden-Fletcher-Goldfrab-Shanno) algorithm, is proposed. Five typical multimodal functions in
the variable space are tested to prove that the new proposed algorithm can quickly converge to the
best point with few function evaluations. In the practical application, the new algorithm is employed
to identify the Young’s modulus of four different materials. The results of the identification further
show that the new proposed algorithm is a very highly efficient and robust one.
A Mixed Integer Efficient Global Optimization Algorithm with Multiple Infill Strategy - Applied to a Wing Topology Optimization Problem