Approximation quality of the hypervolume indicator

Author:

Bringmann Karl,Friedrich Tobias

Publisher

Elsevier BV

Subject

Artificial Intelligence,Linguistics and Language,Language and Linguistics

Reference35 articles.

1. Investigating and exploiting the bias of the weighted hypervolume to articulate user preferences;Auger,2009

2. Theory of the hypervolume indicator: Optimal μ-distributions and the choice of the reference point;Auger,2009

3. HypE: An algorithm for fast hypervolume-based many-objective optimization;Bader;Evolutionary Computation,2011

4. Set-based multi-objective optimization, indicators, and deteriorative cycles;Berghammer,2010

5. SMS-EMOA: Multiobjective selection based on dominated hypervolume;Beume;European Journal of Operational Research,2007

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