An improved small-sample statistical test for comparing the success rates of evolutionary algorithms
Bo Yuan, Marcus Gallagher · 2009
Success rate is a commonly adopted performance criterion for evaluating Evolutionary Algorithms due to their inherent randomness. However, the classical large-sample binomial test based on normal distributions is only valid with a relatively large number of trials, which may not be feasible when experimental studies are very time consuming or expensive. In this paper, we give an alternative statistical test, which is suitable for situations where results from only a small number of trials are available.