To Boldly Show What No One Has Seen Before: A Dashboard for Visualizing Multi-objective Landscapes
This work provides a more accessible tool for researchers and practitioners in multi-objective optimization to visualize and understand complex MOP landscapes, especially for problems with three-dimensional decision spaces.
This paper introduces moPLOT, an R-package that compiles and extends state-of-the-art visualization methods for multi-objective optimization problem (MOP) landscapes, enabling the visualization of three-dimensional decision spaces for the first time. To lower the barrier to entry, it also provides a web-based dashboard for interactive exploration of MOP landscapes using common benchmark functions.
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.