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A New Deterministic Approach Using Sensitivity Region Measures for Multi-Objective Robust and Feasibilty Robust Design Optimization

[+] Author Affiliations
Mian Li, Shapour Azarm

University of Maryland, College Park, MD

Art Boyars

Naval Surface Warfare Center, Indian Head, MD

Paper No. DETC2005-85095, pp. 1233-1242; 10 pages
doi:10.1115/DETC2005-85095
From:
  • ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 2: 31st Design Automation Conference, Parts A and B
  • Long Beach, California, USA, September 24–28, 2005
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 0-7918-4739-X | eISBN: 0-7918-3766-1
  • Copyright © 2005 by ASME

abstract

We present a deterministic, non-gradient based approach that uses robustness measures for robust optimization in multi-objective problems where uncontrollable parameters variations cause variation in the objective and constraint values. The approach is applicable for cases with discontinuous objective and constraint functions, and can be used for objective or feasibility robust optimization, or both together. In our approach, the parameter tolerance region maps into sensitivity regions in the objective and constraint spaces. The robustness measures are indices calculated, using an optimizer, from the sizes of the acceptable objective and constraint variation regions and from worst-case estimates of the sensitivity regions’ sizes, resulting in an outer-inner structure. Two examples provide comparisons of the new approach with a similar published approach that is applicable only with continuous functions. Both approaches work well with continuous functions. For discontinuous functions the new approach gives solutions near the nominal Pareto front; the earlier approach does not.

Copyright © 2005 by ASME
Topics: Design , Optimization

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