Table 6 Results of the multiple-problem Wilcoxon’s test for CMLSP, NRGA, SOO, FWA-DE, OptBees and CCDE at a 0.05 significance level
From: Covariance and crossover matrix guided differential evolution for global numerical optimization
Algorithm | R+ | R− | p value | α = 0.05 |
|---|---|---|---|---|
CCDE vs CMLSP | 296.0 | 169.0 | 1.9808E−01 | No |
CCDE vs NRGA | 432.0 | 3.0 | 1.8626E−08 | Yes |
CCDE vs SOO | 383.0 | 52.0 | 1.3914E−04 | Yes |
CCDE vs FWA-DE | 444.0 | 21.0 | 8.326E−07 | Yes |
CCDE vs OptBees | 458.5 | 6.5 | 3.0739E−08 | Yes |