A pointwise ensemble of surrogates with adaptive function and heuristic formulation

• Published in: Structural and multidisciplinary optimization Vol. 65; no. 4
• Main Authors: Chen, Hao, Li, Weikun, Cui, Weicheng, Liu, Qimeng
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2022; Springer Nature B.V
• Subjects: Computational Mathematics and Numerical Analysis; Design engineering; Engineering; Engineering Design; Heuristic; Model testing; Research Paper; Robustness; Theoretical and Applied Mechanics
• ISSN: 1615-147X; 1615-1488
• DOI: 10.1007/s00158-022-03202-3

Due to the advantages of easy implementation and high efficiency, surrogate models have been widely used in designing complex engineering systems. In general, a stand-alone surrogate model cannot perform well for all engineering design problems, and the performance of a surrogate model is not known in advance. Ensembles of surrogates that combine various stand-alone surrogates have been developed to improve the robustness of stand-alone surrogate models. Inspired by the previous research on using the heuristic formulation to calculate weights of stand-alone surrogate models, we propose a pointwise ensemble of surrogates with adaptive function and heuristic formulation (PEAH) in this paper. The adaptive function presented in this paper contains the local accuracy and prediction uncertainty information around a prediction point. Thus, the adaptive function can adapt to the local characteristics of the prediction point. Various analytical test functions and two engineering design problems have been selected to test PEAH, and existing well-known ensembles of surrogates are employed to compare with the proposed pointwise ensemble model. The test results indicate that PEAH performs better in those problems with a better balance between accuracy and robustness.