Visualisation with treemaps and sunbursts in many-objective optimisation

5Citations
Citations of this article
17Readers
Mendeley users who have this article in their library.

Abstract

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.

Cite

CITATION STYLE

APA

Walker, D. J. (2018). Visualisation with treemaps and sunbursts in many-objective optimisation. Genetic Programming and Evolvable Machines, 19(3), 421–452. https://doi.org/10.1007/s10710-018-9329-0

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free