Research Area: | Research Publication | Year: | 2004 | ||
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Type of Publication: | Technical Report | ||||
Authors: | Agrawal, Gautam; Lewis, Kemper; Chung, C-H K and Huang; Parashar, S; Bloebaum, Chrisitina | ||||
Abstract: | A visualization methodology is presented in which a Pareto Frontier can be visualized in
an intuitive and straightforward manner for an n-dimensional performance space. Based on
this visualization, it is possible to quickly identify ‘good’ regions of the performance and
optimal design spaces for a multi-objective optimization application, regardless of space
complexity. Visualizing Pareto solutions for more than three objectives has long been a
significant challenge to the multi-objective optimization community. The Hyper-space
Diagonal Counting (HSDC) method described here enables the lossless visualization to be
implemented. The proposed method requires no dimension fixing. In this paper, we
demonstrate the usefulness of visualizing n-f space (i.e. for more than three objective
functions in a multiobjective optimization problem). The visualization is shown to aid in the
final decision of what potential optimal design point should be chosen amongst all possible
Pareto solutions. |
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Comments: | Symposium on Multidisciplinary Analysis and Optimization |
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Full text: AIAA-21966-MOP-MDViz-final.pdf
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