| Popis: |
The objective of this study is to propose a methodology which aims at reducing the memory size of hierarchical multilevel models while satisfying both a given accuracy and a maximum computational time, and keeping the initial multilevel structure. In this paper, we propose to construct a new multilevel model satisfying such requirements, based on a choice among available surrogates associated with each submodel. We show how this metamodel assignments can be formulated in an optimal manner through an integer programming problem. The proposed methodology is illustrated on a drag performance model, with surrogates based on High Dimensional Model Representation (HDMR). |
