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Conference object . 2006
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https://doi.org/10.1109/cec.20...
Article . 2006 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object . 2019
Data sources: DBLP
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An Improved Dimension-Sweep Algorithm for the Hypervolume Indicator

Authors: Fonseca, Carlos M.; Paquete, Luis; López-Ibáñez, Manuel;

An Improved Dimension-Sweep Algorithm for the Hypervolume Indicator

Abstract

This paper presents a recursive, dimension-sweep algorithm for computing the hypervolume indicator of the quality of a set of n non-dominated points in d > 2 dimensions. It improves upon the existing HSO (Hypervolume by Slicing Objectives) algorithm by pruning the recursion tree to avoid repeated dominance checks and the recalculation of partial hypervolumes. Additionally, it incorporates a recent result for the three-dimensional special case. The proposed algorithm achieves O(nd−2log n) time and linear space complexity in the worst-case, but experimental results show that the pruning techniques used may reduce the time complexity exponent even further.

Country
Belgium
Keywords

Informatique mathématique

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
227
Top 1%
Top 1%
Top 10%
Green