Visualising the search process for multi-objective optimisation
Author(s)
Helbig, Mardé
Griffith University Author(s)
Year published
2018
Metadata
Show full item recordAbstract
This paper proposes different visualisation techniques to understand the behaviour of an algorithm's entities during the search process when solving multi-objective optimisation problems. A scatter plot is used to highlight the Pareto-ranking of the entities during the search. Different fronts of the entities are indicated through the ball sizes of the scatter plot. Using a parallel coordinate plot for visualising the effect of control parameter values on the performance of an algorithm is also proposed. Possible extensions for dynamic multi-objective optimisation are also discussed.This paper proposes different visualisation techniques to understand the behaviour of an algorithm's entities during the search process when solving multi-objective optimisation problems. A scatter plot is used to highlight the Pareto-ranking of the entities during the search. Different fronts of the entities are indicated through the ball sizes of the scatter plot. Using a parallel coordinate plot for visualising the effect of control parameter values on the performance of an algorithm is also proposed. Possible extensions for dynamic multi-objective optimisation are also discussed.
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Conference Title
GECCO' 18 Companion: Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion
Subject
Theory of computation
Human-computer interaction