Visualising many-objective populations with treemaps
Walker, David J.
Visualising populations of solutions is an important aspect of evolutionary computation (EC), allowing an algorithm user to evaluate the performance of an algorithm and a decision maker to understand the solution set from which they must choose an operating solution. We present a novel approach to visualising multi-objective data, employing treemaps to display both solutions and objectives. We define a simple approach to constructing a tree that can represent a multi-objective population in terms of dominance, and illustrate several ways in which it can be used. Examples are provided that reveal characteristics of objective space, as well as combining information about the parameter space component of the population. The paper concludes with a discussion about the further potential of treemaps within EC.
Copyright © 2015 ACM. This is the accepted, peer-reviewed version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in GECCO Companion '15 Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation. July 11 - 15, 2015, Madrid, Spain. Pages 963-970. ISBN: 978-1-4503-3488-4 doi: 10.1145/2739482.2768445
Proceedings of the 17th International Conference on Genetic and Evolutionary Computation Companion (GECCO 2015), Madrid