Updating exclusive hypervolume contributions cheaply
Several multi-objective evolutionary algorithms compare the hypervolumes of different sets of points during their operation, usually for selection or archiving purposes. The basic requirement is to choose a subset of a front such that the hypervolume of that subset is maximised. We describe a techni...
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Format: | Tagungsbericht |
Sprache: | eng |
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Zusammenfassung: | Several multi-objective evolutionary algorithms compare the hypervolumes of different sets of points during their operation, usually for selection or archiving purposes. The basic requirement is to choose a subset of a front such that the hypervolume of that subset is maximised. We describe a technique that improves the performance of hypervolume contribution based front selection schemes. This technique improves performance by allowing the update of hypervolume contributions after the addition or removal of a point, where these contributions would previously require full recalculation. Empirical evidence shows that this technique reduces runtime by up 72-99% when compared to the cost of full contribution recalculation on DTLZ and random fronts. |
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ISSN: | 1089-778X 1941-0026 |
DOI: | 10.1109/CEC.2009.4982992 |