1. Optimization Methods

1.1 Optimization theories and algorithms

1.2 Design sensitivity analysis and global optimization

1.3 Parallel (or grid) computing in optimization

1.4 Multiobjective optimization

1.5 Probabilistic, heuristic, stochastic, evolutionary methods

2. Shape and Topology Optimization

2.1 Multiscale topology optimization

2.2 Topology optimization of metamaterials

2.3 Topology optimization of advanced materials and smart structures

2.4 Emerging topology and shape optimization techniques in design

2.5 Large-scale topology optimization

2.6 AI-based and data driven shape and topology optimization

2.7 Multi-physics topology optimization

3. Design under Uncertainty

3.1 Uncertainty modeling and uncertainty propagation

3.2 Reliability analysis and reliability-based design optimization

3.3 Robust design optimization

3.4 Model verification and validation 

3.5 Time-dependent reliability analysis and design

4. Approximations, Surrogates, and Metamodeling

4.1 Approximation techniques

4.2 Approximation-based design optimization

4.3 Error and convergence studies

4.4 Model order reduction and benchmarking studies

5. Optimization in Engineering Applications

5.1 Acoustic and vibration problems

5.2 Additive manufacturing

5.3 Health monitoring, damage detection

5.4 Metamaterials

5.5 Multiscale and multiphysics problems

5.6 Noise/vibration suppression and control

5.7 Smart structures and energy harvesting

6. Industrial applications

6.1 Aerospace and aeronautical engineering

6.2 Architecture and civil engineering

6.3 Automotive engineering

6.4 Biomedical engineering

6.5 Electronics and electrical systems 

6.6 Ship/ocean engineering

6.7 Chemical engineering

6.8 Renewable energy (wind, solar, etc.)