An Analysis of Visualisation Techniques for High-Dimensional Pareto Frontiers

Abstract

To explore high-dimensional Pareto frontiers calculated using multi-objective optimisation, analysts rely on visualisation techniques ranging from general-purpose charts to purpose-built dashboards. Prior empirical comparisons were not able to select a single chart type as best practice. Additionally, dashboards are evaluated as complete systems, and no study covers investment portfolio optimisation. We address this gap through a study in which domain experts helped characterise the analytical tasks and served as an initial filter for the techniques we evaluate. We then assessed six visualisation techniques arranged in an interactive dashboard with 57 non-expert and 10 expert participants, across a single-frontier analysis and a frontier comparison on 3D and 6D datasets. The results show that the view choices depend on the task being solved, while no single technique dominates overall in usage or performance. Specialised views stand out on specific tasks, while the tables' role as a robust and easy-to-learn baseline is reinforced by the findings in this study. Our framework is available at: \url{https://github.com/Gunterinos/master_thesis}