Visualizing Solution Sets in Multiobjective Optimization

T. Tušar (Supervised by B. Filipič)

This doctoral research addresses two distinct tasks in visualization in multiobjective optimization—visualization of approximation sets and visualization of empirical attainment functions (EAFs).

In the first task it aims at developing a method for visualizing approximation sets that preserves the Pareto dominance relation between as many visualized points as possible. In addition, it presents a comprehensive review of the existing visualization methods used in evolutionary multiobjective optimization, showing their outcomes on two novel 4D benchmark approximation sets. In the second task the research addresses the visualization of exact as well as approximated 3D EAF values and differences in these values provided by two competing multiobjective optimization algorithms.

Project accomplished with a successful Ph.D. dissertation defense in September 2014.