Intuitive Visualization of Pareto Frontier for Multi- Objective Optimization in n-Dimensional Performance Space
نویسندگان
چکیده
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.
منابع مشابه
Estimation of Multi-Objective Pareto Frontier using Hyperspace Diagonal Counting
The Hyper-Space Diagonal Counting (HSDC) method was previously proposed for generating representations of n-dimensional data in 2or 3-dimensions. Since its inception, the HSDC has been used to visualize the n-dimensional performance space in an intuitive fashion for Multiobjective Optimization Applications, through the incorporation of the HSDC into the Hyperspace Pareto Frontier (HPF) visualiz...
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