PAVED: Pareto Front Visualization for Engineering Design
Authors: Lena Cibulski, Hubert Mitterhofer, Thorsten May and Jörn Kohlhammer
Demo:
[ Ссылка ]
Presented at EuroVis2020
Full paper: [ Ссылка ]
Design problems in engineering typically involve a large solution space and several potentially conflicting criteria. Selecting a compromise solution is often supported by optimization algorithms that compute hundreds of Pareto-optimal solutions, thus informing a decision by the engineer. However, the complexity of evaluating and comparing alternatives increases with the number of criteria that need to be considered at the same time. We present a design study on Pareto front visualization to support engineers in applying their expertise and subjective preferences for selection of the most-preferred solution. We provide a characterization of data and tasks from the parametric design of electric motors. The requirements identified were the basis for our development of PAVED, an interactive parallel coordinates visualization for exploration of multi-criteria alternatives. We reflect on our user-centered design process that included iterative refinement with real data in close collaboration with a domain expert as well as a summative evaluation in the field. The results suggest a high usability of our visualization as part of a real-world engineering design workflow. Our lessons learned can serve as guidance to future visualization developers targeting multi-criteria optimization problems in engineering design or alternative domains.
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Literature mentioned in the video:
[Sedlmair et al., 2012]: Sedlmair M., Meyer M., Munzner T.: Design study methodology: reflections from the trenches and the stacks. IEEE Transactions on Visualization and Computer Graphics 18, 12 (2012), 2431-2440.
[Dimara et al., 2017]: Dimara E., Bezerianos A., Dragicevic P.: Conceptual and methodological issues in evaluating multidimensional visualizations for decision support. IEEE Transactions on Visualization and Computer Graphics 24, 1 (2017), 749-759.
[Payne et al., 1993]: Payne J. W., Payne J. W., Bettman J. R., Johnson E. J.: The adaptive decision maker. Cambridge University Press, 1993.
[Meyer & Dykes, 2009]: Meyer M., Dykes J.: Criteria for rigor in visualization design study. IEEE TVCG, 2019.
Pictures:
[1]: „E-Twow Electric Motor“ by Kaspars Dambis, licensed under CC BY 2.0
[2]: symspace.lcm.at
[3]: „letterbox“ by ubrog, licensed under CC BY-NC 2.0
