Visualising high-dimensional Pareto relationships in two-dimensional scatterplots

Abstract

Copyright © 2013 Springer-Verlag Berlin Heidelberg. The final publication is availablevia the DOI in this recordBook title: Evolutionary Multi-Criterion Optimization7th International Conference on Evolutionary Multi-Criterion Optimization (EMO 2013), Sheffield, UK, March 19-22, 2013The codebase for this paper is available at https://github.com/fieldsend/emo_2013_vizIn this paper two novel methods for projecting high dimensional data into two dimensions for visualisation are introduced, which aim to limit the loss of dominance and Pareto shell relationships between solutions to multi-objective optimisation problems. It has already been shown that, in general, it is impossible to completely preserve the dominance relationship when mapping from a higher to a lower dimension – however, approaches that attempt this projection with minimal loss of dominance information are useful for a number of reasons. (1) They may represent the data to the user of a multi-objective optimisation problem in an intuitive fashion, (2) they may help provide insights into the relationships between solutions which are not immediately apparent through other visualisation methods, and (3) they may offer a useful visual medium for interactive optimisation. We are concerned here with examining (1) and (2), and developing relatively rapid methods to achieve visualisations, rather than generating an entirely new search/optimisation problem which has to be solved to achieve the visualisation– which may prove infeasible in an interactive environment for real time use. Results are presented on randomly generated data, and the search population of an optimiser as it progresses. Structural insights into the evolution of a set-based optimiser that can be derived from this visualisation are also discussed