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This is a repository that collects various data-driven evolutionary algorithms (DDEA).

Model Paper Original Repository
DDEA-SE Offline data-driven evolutionary optimization using selective surrogate ensembles HandingWang/DDEA-SE
CALSAPSO Committee-based Active Learning for Surrogate-Assisted Particle Swarm Optimization of Expensive Problems HandingWang/CALSAPSO
MGPSLPSO Multiobjective Infill Criterion Driven Gaussian Process-Assisted Particle Swarm Optimization of High-Dimensional Expensive Problems Jetina/MGPSLPSO
SRK-DDEA Ranking for Offline Data-Driven Evolutionary Optimization Using Radial Basis Function Networks with Multiple Kernels Mikasa210/SRK-DDEA
CA-LLSO A Classifier-Assisted Level-Based Learning Swarm Optimizer for Expensive Optimization CarrieWei/CA-LLSO_Code
TT-DDEA Offine Data-Driven Evolutionary Optimization Based on Tri-Training, Swarm and Evolutionary Computation Mikasa210/TT-DDEA
RF-CMOCO A Random Forest-Assisted Evolutionary Algorithm for Data-Driven Constrained Multiobjective Combinatorial Optimization of Trauma Systems HandingWang/RF-CMOCO
K-RVEA A surrogate-assisted reference vector guided evolutionary algorithm for computationally expensive many-objective optimization tichugh/K-RVEA
HK-RVEA Surrogate-assisted evolutionary biobjective optimization for objectives with non-uniform latencies tichugh/HK-RVEA
TSA-BFEA Transfer stacking from low-to high-fidelity: A surrogate-assisted bi-fidelity evolutionary algorithm HandingWang/TSA-BFEA

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