Visualisation with treemaps and sunbursts in evolutionary many-objective optimisation
Genetic Programming and Evolvable Machines
Reason for embargo
Currently under an indefinite embargo pending publication by Springer Verlag. 12 month embargo to be applied on publication.
Visualisation is an important aspect of evolutionary computation, enabling practitioners to explore the operation of their algorithms in an intuitive way and providing a better means for displaying their results to problem owners. The presentation of the complex data arising in many-objective evolutionary algorithms remains a challenge, and this work examines the use of treemaps and sunbursts for visualising such data. We present a novel algorithm for arranging a treemap so that it explicitly displays the dominance relations that characterise many-objective populations, as well as considering approaches for creating trees with which to represent multi- and many objective solutions. We show that treemaps and sunbursts can be used to display important aspects of evolutionary computation, such as the diversity and convergence of a search population, and demonstrate the approaches on a range of test problems and a real-world problem from the literature.
Supported by EPSRC grant EP/P009441/1 for some of this work.
This is the author accepted manuscript.
Awaiting citation and DOI.