Ordinal optimization techniques help us locating "good" designs efficiently
. previous studies of ordinal optimization define the "good" designs as tho
se being tops in the "order" of performance. In this study, we argue that w
ith the help of practical Drier knowledge and observations, we can establis
h quantitative: relationship between the good design found and the performa
nce "values" of it. Therefore, the analysis of ordinal optimization can be
carried out to identify designs that are good by some criterion of their pe
rformance "values".