Initial Results of an MDO Method Evaluation Study

The NASA Langley MDO method evaluation study seeks to arrive at a set of guidelines for using promising MDO methods by accumulating and analyzing computational data for such methods. The data are collected by conducting a series of reproducible experiments. In the first phase of the study, three MDO methods were implemented in the iSIGHT* framework and used to solve a set of ten relatively simple problems. In this paper, we comment on the general considerations for conducting method evaluation studies and report some initial results obtained to date. In particular, although the results are not conclusive because of the small initial test set, preliminary numbers suggest that the performance of the methods tends to be consistent with their predicted theoretical properties.

[1]  Leon S. Lasdon,et al.  Optimization Theory of Large Systems , 1970 .

[2]  David A. Wismer,et al.  Optimization methods for large-scale systems ... with applications , 1971 .

[3]  Ilan Kroo,et al.  Implementation and Performance Issues in Collaborative Optimization , 1996 .

[4]  Ilan Kroo,et al.  Collaborative optimization using response surface estimation , 1998 .

[5]  L Padula Sharon,et al.  MDO Test Suite at NASA Langley Research Center , 1996 .

[6]  Guoliang Xue,et al.  The MINPACK-2 test problem collection , 1992 .

[7]  E. J.,et al.  MULTILEVEL ALGORITHMS FOR NONLINEAR OPTIMIZATION , 2022 .

[8]  Howard M. Adelman,et al.  Recent advances in integrated multidisciplinary optimization of rotorcraft , 1992 .

[9]  J. Dennis,et al.  Multilevel algorithms for nonlinear optimization , 1995 .

[10]  M Alexandrov Natalia,et al.  Analytical and Computational Aspects of Collaborative Optimization , 2000 .

[11]  Robert D. Braun,et al.  Collaborative optimization: an architecture for large-scale distributed design , 1996 .

[12]  Yuan Charles,et al.  Evaluation of Methods for Multidisciplinary Design Optimization (MDO), Part II , 2000 .

[13]  G. R. Shubin.  Application of alternative multidisciplinary optimization formulations to a model problem for static aeroelasticity , 1995 .

[14]  J. Dennis,et al.  A New Nonlinear Equations Test Problem , 1986 .

[15]  John E. Dennis,et al.  Problem Formulation for Multidisciplinary Optimization , 1994, SIAM J. Optim..

[16]  Panos M. Pardalos,et al.  A Collection of Test Problems for Constrained Global Optimization Algorithms , 1990, Lecture Notes in Computer Science.

[17]  George L. Nemhauser.  Optimization theory for large systems , 1972 .

[18]  Robert Michael Lewis,et al.  Practical Aspects Of Variable Reduction Formulations And Reduced Basis Algorithms In Multidisciplina , 1995 .

[19]  N. Alexandrov.  Multilevel algorithms for nonlinear equations and equality constrained optimization , 1993 .

[20]  Jaroslaw Sobieszczanski-Sobieski,et al.  Optimization by decomposition: A step from hierarchic to non-hierarchic systems , 1989 .

[21]  Ilan Kroo,et al.  Collaborative optimization using response surface estimation , 1998 .