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Assessing the Effectiveness of Using Graveyard Data for Generating Design Alternatives

[+] Author Affiliations
Garrett Foster, Scott Ferguson

North Carolina State University, Raleigh, NC

Paper No. DETC2011-48636, pp. 563-576; 14 pages
  • ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 5: 37th Design Automation Conference, Parts A and B
  • Washington, DC, USA, August 28–31, 2011
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5482-2
  • Copyright © 2011 by ASME


Modeling to Generate Alternatives (MGA) is a technique used to identify variant designs that maximize design space distance from an initial point while satisfying performance loss constraints. Recent work has explored the application of this technique to nonlinear design problems, where the design space was investigated using an exhaustive sampling procedure. While computational cost concerns were noted, the main focus was determining how scaling and distance metric selection influenced alternative discovery. To increase the viability of MGA for engineering design problems, this work looks to reduce the computational overhead needed to identify design alternatives. This paper investigates and quantifies the effectiveness of using previously sampled designs, i.e. a graveyard, from a multiobjective genetic algorithm as a means of reducing computational expense. Computational savings and the expected error are quantified to assess the effectiveness of this approach. These results are compared to other more common “search” techniques; namely Latin hypercube samplings, grid search, and the Nelder-Mead simplex method. The performance of these “search” techniques are subsequently explored in two case study problems — the design of a two bar truss, and an I-beam — to find the most unique alternative design over a range of different thresholds. Results from this work show the graveyard can be used as a way of inexpensively generating alternatives that are close to ideal, especially nearer to the starting design. Additionally, this paper demonstrates that graveyard information can be used to increase the performance of the Nelder-Mead simplex method when searching for alternative designs.

Copyright © 2011 by ASME
Topics: Design



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