1 Introduction  
2 Background Knowledge  
2.1 Basic Concepts  
2.2 Tutorial of Vanilla MOEA/D  
3 Selected Developments on Major Components of MOEA/D  
3.1 Weight Vector Setting  
3.2 Subproblem Formulations  
3.3 Selection Mechanisms in MOEA/D  
3.4 Reproduction Operators in MOEA/D  
4 Advanced Topics  
4.1 Constraint Handling  
4.2 Optimization in Dynamic and Uncertain Environments  
4.3 Surrogate-Assisted Methods for Expensive Optimization  
4.4 Preference Incorporation in MOEA/D  
5 Emerging Topics and Future Directions  
5.0.1 Large-scale MOPs (LSMOPs)  
5.0.2 Multimodal MOPs (MMOPs)  
5.0.3 Variable-length MOPs  
5.0.4 Sparse optimization  
5.0.5 Parallel computing  
5.0.6 Multi-agent system vs MOEA/D  
5.0.7 Theoretical studies  
6 Concluding Remarks