Evaluating the performance of visual steering commands for user-guided pareto frontier sampling during trade space exploration

Dan Carlsen, Matthew Malone, Josh Kollat, Timothy William Simpson

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

2 Scopus citations

Abstract

Trade space exploration is a promising decision-making paradigm that provides a visual and more intuitive means for formulating, adjusting, and ultimately solving design optimization problems. This is achieved by combining multidimensional data visualization techniques with visual steering commands to allow designers to "steer" the optimization process while searching for the best, or Pareto optimal, designs. In this paper, we compare the performance of different combinations of visual steering commands implemented by two users to a multi-objective genetic algorithm that is executed "blindly" on the same problem with no human intervention. The results indicate that the visual steering commands -regardless of the combination in which they are invoked -provide a 4x -7x increase in the number of Pareto solutions that are obtained when the human is "in-the-loop" during the optimization process. As such, this study provides the first empirical evidence of the benefits of interactive visualization-based strategies to support engineering design optimization and decision-making. Future work is also discussed.

Original languageEnglish (US)
Title of host publication2008 Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC 2008
Pages500-510
Number of pages11
Volume1
EditionPART A
StatePublished - Nov 23 2009
Event2008 ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC 2008 - New York City, NY, United States
Duration: Aug 3 2008Aug 6 2008

Other

Other2008 ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC 2008
CountryUnited States
CityNew York City, NY
Period8/3/088/6/08

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Industrial and Manufacturing Engineering
  • Mechanical Engineering

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