Research Areas
Research Areas
The research areas of SOLab include Management Science, Optimization, Data-centric AI, Machine Learning, Deep Learning, and their applications including but not limited to the following:
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1. Optimization of Last-Mile Transportation Systems
The themes are
- Last-mile delivery considering backhaul
- Vehicle routing problem with heterogeneous delivery vehicles
- Delivery station using heterogeneous delivery vehicles
- Cold chain last-mile delivery
- Underground delivery
- Location problem for UAV vertipad
- Mobile delivery station
- Battery swapping stations for UAVs
2. Optimization of Healthcare System Operations
The themes are
- Prediction and utilization of emergency room stay duration based on machine learning (MIMIC-IV data)
- Prediction of ICU readmissions and classification of critical care patients based on machine learning (MIMIC-IV data)
- Location problem for UAV vertipad for cardiac arrest patients
3. Supply Chain Optimization
The theme is
- Logistics optimization strategies for mature products
4. Efficiency in Business Decision-Making
The themes are
- Machine learning-based corporate environmental controversy prediction model
- Production design efficiency model
- Prediction of companies' export potential using machine learning
- Machine learning-based aircraft climb rate modeling for fuel efficiency improvement
- Improving the accuracy of castings classification using generative adversarial networks (GAN)
- Development of an alternative viewership measurement model
5. Systematization of Investment Decisions
The themes are
- US IPO Underpricing prediction model using natural language processing (NLP)
- Machine learning-based decision support for venture capital investments
- Portfolio optimization
6. Development of Optimization and Heuristic Methodologies
The themes are
- Quantum-inspired genetic algorithm
- Effective problem-specific heuristic design
- Efficient combinatorial optimization modeling based on analytics
- Decomposition techniques
- Sample average approximation for stochastic optimization
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