English

To Boldly Show What No One Has Seen Before: A Dashboard for Visualizing Multi-objective Landscapes

Neural and Evolutionary Computing 2020-12-01 v1 Optimization and Control

Abstract

Simultaneously visualizing the decision and objective space of continuous multi-objective optimization problems (MOPs) recently provided key contributions in understanding the structure of their landscapes. For the sake of advancing these recent findings, we compiled all state-of-the-art visualization methods in a single R-package (moPLOT). Moreover, we extended these techniques to handle three-dimensional decision spaces and propose two solutions for visualizing the resulting volume of data points. This enables - for the first time - to illustrate the landscape structures of three-dimensional MOPs. However, creating these visualizations using the aforementioned framework still lays behind a high barrier of entry for many people as it requires basic skills in R. To enable any user to create and explore MOP landscapes using moPLOT, we additionally provide a dashboard that allows to compute the state-of-the-art visualizations for a wide variety of common benchmark functions through an interactive (web-based) user interface.

Keywords

Cite

@article{arxiv.2011.14395,
  title  = {To Boldly Show What No One Has Seen Before: A Dashboard for Visualizing Multi-objective Landscapes},
  author = {Lennart Schäpermeier and Christian Grimme and Pascal Kerschke},
  journal= {arXiv preprint arXiv:2011.14395},
  year   = {2020}
}

Comments

This version has been accepted for publication at the 11th International Conference on Evolutionary Multi-Criterion Optimization (EMO 2021)

R2 v1 2026-06-23T20:34:49.134Z