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This paper makes an approach to the approximate optimum in structural design, which combines the global response surface (GRS)
based multivariate adaptive regression splines (MARS) with Move-Limit strategy (MLS). MARS is an adaptive regression process,
which fits in with the multidimensional problems. It adopts a modified recursive partitioning strategy to simplify high-dimensional
problems into smaller highly accurate models. MLS for moving and resizing the search sub-regions is employed in the space
of design variables. The quality of the approximation functions and the convergence history of the optimization process are
reflected in MLS. The disadvantages of the conventional response surface method (RSM) have been avoided, specifically, highly
nonlinear high-dimensional problems. The GRS/MARS with MLS is applied to a high-dimensional test function and an engineering
problem to demonstrate its feasibility and convergence, and compared with quadratic response surface (QRS) models in terms
of computational efficiency and accuracy. 相似文献
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