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Evolutionary Diversity Optimization Using Multi-Objective Indicators
November 16, 2018 · Declared Dead · 🏛 Annual Conference on Genetic and Evolutionary Computation
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Authors
Aneta Neumann, Wanru Gao, Markus Wagner, Frank Neumann
arXiv ID
1811.06804
Category
cs.NE: Neural & Evolutionary
Citations
57
Venue
Annual Conference on Genetic and Evolutionary Computation
Last Checked
1 month ago
Abstract
Evolutionary diversity optimization aims to compute a diverse set of solutions where all solutions meet a given quality criterion. With this paper, we bridge the areas of evolutionary diversity optimization and evolutionary multi-objective optimization. We show how popular indicators frequently used in the area of multi-objective optimization can be used for evolutionary diversity optimization. Our experimental investigations for evolving diverse sets of TSP instances and images according to various features show that two of the most prominent multi-objective indicators, namely the hypervolume indicator and the inverted generational distance, provide excellent results in terms of visualization and various diversity indicators.
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