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Visualization of Pareto Solutions by Spherical Self-Organizing Map and It’s acceleration on a GPU

Masato Yoshimi, Takuya Kuhara, Kaname Nishimoto, Mitsunori Miki, Tomoyuki Hiroyasu
Factuly of Engineering, Doshisha University, Kyoto, Japan
Journal of Software Engineering and Applications (JSEA), Vol.5 No.3, 2012

@article{yoshimi2012visualization,

   title={Visualization of Pareto Solutions by Spherical Self-Organizing Map and It’s acceleration on a GPU},

   author={Yoshimi, M. and Kuhara, T. and Nishimoto, K. and Miki, M. and Hiroyasu, T.},

   journal={Journal of Software Engineering and Applications},

   volume={5},

   number={3},

   pages={129–137},

   year={2012},

   publisher={Scientific Research Publishing}

}

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In this study, we visualize Pareto-optimum solutions derived from multiple-objective optimization using spherical self-organizing maps (SOMs) that lay out SOM data in three dimensions. There have been a wide range of studies involving plane SOMs where Pareto-optimal solutions are mapped to a plane. However, plane SOMs have an issue that similar data differing in a few specific variables are often placed at far ends of the map, compromising intuitiveness of the visualization. We show in this study that spherical SOMs allow us to find similarities in data otherwise undetectable with plane SOMs. We also implement and evaluate the performance using parallel sphere processing with several GPU environments.
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