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Design Preference Elicitation Using Efficient Global Optimization

[+] Author Affiliations
Yi Ren, Panos Y. Papalambros

University of Michigan, Ann Arbor, MI

Paper No. DETC2011-48316, pp. 591-600; 10 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


We seek to elicit individual design preferences through user-computer interaction. During an iteration of the interactive session, the computer presents a set of designs to the user who then picks any preferred designs from the set. The computer learns from this feedback and creates the next set of designs using its accumulated knowledge to minimize a merit function. Under the hypothesis that user responses are deterministic, we show that an effective query scheme is akin to the Efficient Global Optimization (EGO) algorithm. Using simulated interactions, we discuss how the merit function form and user preference sensitivity can affect search efficiency and hence the time to complete an interactive session. We demonstrate the proposed algorithm in the design of vehicle exteriors.

Copyright © 2011 by ASME
Topics: Design , Optimization



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