In response to the problem of poor universality in limiting the widespread application of surrogate model technology in engineering problems, a method for adaptive selection of surrogate models is proposed based on a systematic understanding of the theory and development of surrogate model technology. This method is combined with sequential iterative optimization of surrogate models to form an efficient optimization method with strong universality. Secondly, numerical experiments were conducted on this method using standard test functions to verify its feasibility and superiority in optimization efficiency. Finally, the proposed method is applied to the optimization design of products to verify its feasibility and superiority in practical engineering problems.
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