Performance Measures on Jumping Gene - Multiobjective Optimization Methodology: A Jumping Gene Approach - page 106

Table 5.7
Means.and.Standard.Deviations.of.the.Spread.for.Unconstrained.Test.Functions.with.Real.
Number.Coding
Test
Function MOGA NPGA2 NSGA2 SPEA2 PAES MICROGA JG
ZIT1 0.56998 0.56315 0.54173 0.56256 0.71198 0.83987 0.51694
(real) (0.05726) (0.04825) (0.05107) (0.04346) (0.15148) (0.04098) (0.06099)
ZIT2 0.69375 0.65685 0.65005 0.66054 0.70422 0.90731 0.57713
(real) (0.05570) (0.05319) (0.06307) (0.04572) (0.10218) (0.03819) (0.06253)
ZIT3 0.66761 0.67783 0.66309 0.68165 0.70329 0.82258 0.66627
(real) (0.07318) (0.05143) (0.06146) (0.06935) (0.08939) (0.04561) (0.07855)
ZIT4 0.90134 0.83851 0.70980 0.81572 1.16767 0.87446 0.36373
(real) (0.13221) (0.10636) (0.14454) (0.14291) (0.27960) (0.09259) (0.06138)
ZIT6 0.99920 0.99063 1.00089 1.03269 1.13532 0.92468 0.95879
(real) (0.04478) (0.03754) (0.03752) (0.06267) (0.08332) (0.02896) (0.08229)
Source: . Data.from.Chan,.T..M.,.Man,.K..F.,.Kwong,.S.,.Tang,.K..S.,.A.jumping.gene.paradigm.for.evolutionary.
multiobjective.optimization,. IEEETransactionsonEvolutionaryComputation ,.12(2),.143-159,.2008.
Note: . The.best.result.for.each.test.function.is.marked.in.bold,.and.the.values.in.parentheses.represent.the.
standard.deviation.