Diagnostic analysis of metamodels' multivariate dependencies and their impacts in many-objective design optimization

Matthew J. Woodruff, Timothy William Simpson, Patrick M. Reed

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

While computers are continually getting faster, physical models of complex systems grow more sophisticated and keep pace. Using metamodels can dramatically reduce the time it takes to evaluate a solution for a complex system; however, while the chief virtue of metamodels is that they approximate more computationally expensive models, this is also their main drawback. Metamodels are approximations, and as such they behave differently than the more sophisticated models they approximate. While the metamodels may be accurate approximations, they may also introduce new interdependencies in the response outputs that may hinder search algorithms during optimization. Understanding the impact of the approximation on the subsequent search thus becomes an important part of the problem as models that were computationally expensive ten to fifteen years ago may now run fast enough for use in optimization. In this paper, we use Sobol0 global sensitivity analysis to compare the search performance of a new auto-adaptive many objective evolutionary algorithm solving a challenging product family design problem with both the original analysis and a second-order response surface approximation of the original analysis. Interdependencies in the response outputs are found to result from the problem formulation used rather than the underlying model in this case. Search operator selection by the auto-adaptive evolutionary algorithm is shown to be consistent with the model sensitivities found by global sensitivity analysis.

Original languageEnglish (US)
Title of host publication39th Design Automation Conference
PublisherAmerican Society of Mechanical Engineers
ISBN (Print)9780791855898
DOIs
StatePublished - Jan 1 2013
EventASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2013 - Portland, OR, United States
Duration: Aug 4 2013Aug 7 2013

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume3 B

Other

OtherASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2013
CountryUnited States
CityPortland, OR
Period8/4/138/7/13

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Mechanical Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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    Woodruff, M. J., Simpson, T. W., & Reed, P. M. (2013). Diagnostic analysis of metamodels' multivariate dependencies and their impacts in many-objective design optimization. In 39th Design Automation Conference [V03BT03A015] (Proceedings of the ASME Design Engineering Technical Conference; Vol. 3 B). American Society of Mechanical Engineers. https://doi.org/10.1115/DETC2013-13125