Aiaa on Managing the Use of Surrogates in General Nonlinear Optimization and Mdo

This paper is concerned with a trust region ap proximationmanagement framework AMF for solv ing the nonlinear programming problem in general and multidisciplinary optimization problems in par ticular The intent of the AMF methodology is to facilitate the solution of optimization problems with high delity models While such models are designed to approximate the physical phenomena they describe to a high degree of accuracy their use in a repetitive procedure for example iterations of an optimization or a search algorithm make such use prohibitively expensive An improvement in design with lower delity cheaper models however does not guar antee a corresponding improvement for the higher delity problem The AMF methodology proposed here is based on a class of multilevel methods for con strained optimization and is designed to manage the use of variable delity approximations or models in a systematic way that assures convergence to critical points of the original high delity problem