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ResearchFormerly WizWand

Offline Data-driven Multi-Objective Optimization on DTLZ1-DTLZ7 and Omnitest Suite

2.42Overall RanksGPR(Matern)+DR
2.20843.63675.0656.4933Nov 9, 2025
Updated 6mo ago

Evaluation results

MethodLinks
GPR(Matern)+DRTraining sample size=1,000, Dual-ranking (DR) strategy=true, tau parameter=0.9, Base optimization algorithm=NSGA-II (omitted)2025.112.42
GPR(RBF)+DRTraining sample size=1,000, Dual-ranking (DR) strategy=true, tau parameter=0.9, Base optimization algorithm=NSGA-II (omitted)2025.112.5
GPR(Matern)+DROptimizer=NSGA-II, Dual-ranking (DR) strategy=true, Tau (τ)=0.9, Kernel=Matern2025.113.25
IBEA-MSOptimizer=NSGA-II, Dual-ranking (DR) strategy=true, Tau (τ)=0.92025.113.38
IBEA-MSTraining sample size=1,000, Dual-ranking (DR) strategy=false, tau parameter=0.9, Base optimization algorithm=NSGA-II (omitted)2025.113.48
TGPR-MOOptimizer=NSGA-II, Dual-ranking (DR) strategy=true, Tau (τ)=0.92025.113.5
QR+DRTraining sample size=1,000, Dual-ranking (DR) strategy=true, tau parameter=0.9, Base optimization algorithm=NSGA-II (omitted)2025.113.5
TGPR-MOTraining sample size=1,000, Dual-ranking (DR) strategy=false, tau parameter=0.9, Base optimization algorithm=NSGA-II (omitted)2025.114.25
GPR(RBF)+DROptimizer=NSGA-II, Dual-ranking (DR) strategy=true, Tau (τ)=0.9, Kernel=RBF2025.114.67
Prob-RVEAOptimizer=NSGA-II, Dual-ranking (DR) strategy=true, Tau (τ)=0.92025.115.17
QR+DROptimizer=NSGA-II, Dual-ranking (DR) strategy=true, Tau (τ)=0.92025.115.17
DDMOEA/GANTraining sample size=1,000, Dual-ranking (DR) strategy=false, tau parameter=0.9, Base optimization algorithm=NSGA-II (omitted)2025.115.92
DDMOEA/GANOptimizer=NSGA-II, Dual-ranking (DR) strategy=true, Tau (τ)=0.92025.116
BNN+DRTraining sample size=1,000, Dual-ranking (DR) strategy=true, tau parameter=0.9, Base optimization algorithm=NSGA-II (omitted)2025.116.04
Prob-MOEA/DOptimizer=NSGA-II, Dual-ranking (DR) strategy=true, Tau (τ)=0.92025.116.12
BNN+DROptimizer=NSGA-II, Dual-ranking (DR) strategy=true, Tau (τ)=0.92025.116.38
Prob-MOEA/DTraining sample size=1,000, Dual-ranking (DR) strategy=false, tau parameter=0.9, Base optimization algorithm=NSGA-II (omitted)2025.117.21
Prob-RVEATraining sample size=1,000, Dual-ranking (DR) strategy=false, tau parameter=0.9, Base optimization algorithm=NSGA-II (omitted)2025.117.71