1.1 Optimization theory and algorithms
1.2 Design sensitivity analysis and global optimization
1.3 Parallel, grid, and high-performance computing in optimization
1.4 Multi-objective optimization
1.5 Heuristic and evolutionary methods
2.1 Size optimization
2.2 Shape optimization
2.3 Topology optimization: theory and methodology
2.4 Topology optimization: applications
3.1 Artificial intelligence, machine learning, and deep learning
3.2 Generative design
3.3 Agent- and LLM-based analysis and design
3.4 Physics-informed AI modeling
4.1 Uncertainty quantification and propagation
4.2 Reliability analysis and reliability-based design optimization
4.3 Robust design optimization
4.4 Model verification and validation
4.5 Time-dependent reliability analysis and design
5.1 Approximation techniques
5.2 Surrogate-based design optimization
5.3 Error and convergence study
5.4 Model order reduction and benchmarking studies
6.1 Decomposition methods
6.2 Coordination strategies (architectures)
6.3 MDO applications
7.1 Aerospace, automotive, and mobility systems
7.2 Architectural, civil, and structural engineering
7.3 Mechanical, manufacturing, and process engineering
7.4 Bioinspired, biomedical, and healthcare systems
7.5 Energy, environmental, and sustainable technologies
7.6 Smart and advanced systems