abstract = "Evolutionary Computation has been dogged by a central
statistical issue: how does one fairly compare the
performance of two techniques which differ in the
amount of work required? While Koza's computational
effort statistic attempts to answer this problem, it is
a point statistic and has other statistical problems.
We present the y-test, a statistical test which takes
as input a set of outcomes from the observed runs of
two processes A and B. The y-test synthetically
performs a work-balanced comparison between k runs of A
and l runs of B. We show that by choosing k and l
appropriately, we can compensate for the fact that one
of the processes is computationally more efficient than
the other.",
notes = "WCCI 2006 - A joint meeting of the IEEE, the EPS, and
the IEE.