Towards fast approximations for the hypervolume indicator for multi-objective optimization problems by Genetic Programming

Hypervolume (HV) has become one of the most popular indicators to assess the quality of Pareto front approximations. However, the best algorithm for computing these values has a computational complexity of O(Nk/3polylog(N)) for N candidate solutions and k objectives. In this study, we propose a regr...

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Veröffentlicht in:	Applied soft computing Jg. 125; S. 109103
Hauptverfasser:	Sandoval, Cristian, Cuate, Oliver, González, Luis C., Trujillo, Leonardo, Schütze, Oliver
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.08.2022
Schlagworte:	Automatic algorithm design Genetic programming Hypervolume Multi-objective optimization Regression Regression Multi-objective optimization Genetic programming Automatic algorithm design Hypervolume
ISSN:	1568-4946, 1872-9681
Online-Zugang:	Volltext
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