Sample size calculations for the experimental comparison of multiple algorithms on multiple problem instances

This work presents a statistically principled method for estimating the required number of instances in the experimental comparison of multiple algorithms on a given problem class of interest. This approach generalises earlier results by allowing researchers to design experiments based on the desire...

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Veröffentlicht in:	Journal of heuristics Jg. 26; H. 6; S. 851 - 883
Hauptverfasser:	Campelo, Felipe, Wanner, Elizabeth F.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.12.2020 Springer Nature B.V
Schlagworte:	Algorithms Artificial Intelligence Calculus of Variations and Optimal Control; Optimization Management Science Mathematical analysis Mathematics Mathematics and Statistics Operations Research Operations Research/Decision Theory Simulated annealing Iterative sampling Statistical methods Multiple hypotheses testing Sample size estimation Experimental comparison of algorithms
ISSN:	1381-1231, 1572-9397
Online-Zugang:	Volltext
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