The Design of Open Engineering Systems Lab

University at Buffalo - The State University of New York

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Intuitive Visualization of Pareto Frontier for Multi-Objective Optimization in n-Dimensional Performance Space

Research Area: Research Publication Year: 2004
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.
Comments:
Symposium on Multidisciplinary Analysis and Optimization

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