1 Introduction
2 Meta-analysis of Multi-Fidelity Optimization Literature: A Text Mining Approach
2.1 Text Mining Framework
2.2 Text Mining Results
3 Multi-Fidelity Surrogate Modeling
3.1 Single Model Methods
3.2 Space-Mapping Methods
3.3 Correction-based Methods
3.4 Auto Regressive-based (AR1) Methods
3.5 Multi-task Gaussian Process (MTGP) Methods
3.6 Nonlinear Hierarchical Methods
3.7 Multi-Fidelity Physics-Informed Neural Networks (PINNs)
3.8 Discussions
4 Optimizer for Multi-Fidelity Optimization
4.1 Bayesian Optimization for Multi-Fidelity Optimization
4.2 Surrogate-Assisted Evolutionary Algorithms for Multi-Fidelity Optimization
4.3 Bandit-based Algorithms for Multi-Fidelity Optimization
4.4 Discussions
5 Fidelity Management Strategies
5.1 Fixed Methods
5.2 Adaptive Methods
5.3 Discussions
6 Benchmark Test Problems in Multi-Fidelity Optimization
6.1 Discussions
7 Applications of Multi-Fidelity Optimization
7.1 Applications on Hyperparameter Optimization (HPO)
7.2 Engineering Design and Optimization
7.3 Applications in Scientific Discovery
7.4 Applications of Multi-Fidelity Physics-Informed Neural Networks
8 Challenges and Future Opportunities
8.1 Scalability of MFO
8.2 Balancing Cost and Accuracy in Lower Fidelity Models
8.3 Human-in-the-loop Optimization
8.4 Near Real-World Benchmarks
8.5 Reproducible Research
9 Conclusion