Research

Publications

1. Alcántara, A., & Ruiz, C. (2024). Optimal day-ahead offering strategy for large producers based on market price response learning. European Journal of Operational Research, 319(3), 891-907.
2. Alcántara, A., & Ruiz, C. (2023). A neural network-based distributional constraint learning methodology for mixed-integer stochastic optimization. Expert Systems with Applications, 232, 120895.
3. Alcántara, A., & Ruiz, C. (2023). On data-driven chance constraint learning for mixed-integer optimization problems. Applied Mathematical Modelling, 121, 445-462.
4. Alcantara, A., Galván, I. M., & Aler, R. (2023). Deep neural networks for the quantile estimation of regional renewable energy production. Applied Intelligence, 53(7), 8318-8353.
5. Alcántara, A., Galván, I. M., & Aler, R. (2023). Pareto optimal prediction intervals with hypernetworks. Applied Soft Computing, 133, 109930.
6. Alcántara, A., Galván, I. M., & Aler, R. (2022). Direct estimation of prediction intervals for solar and wind regional energy forecasting with deep neural networks. Engineering Applications of Artificial Intelligence, 114, 105128.

Working papers

• Alcántara, A., Diaz-Cachinero, P., Sánchez-González, A., & Ruiz, C. (2024). Leveraging Neural Networks to Optimize Heliostat Field Aiming Strategies in Concentrating Solar Power Tower Plants arXiv preprint arXiv:2412.16995
• Alcántara, A., Ruiz, C., & Tsay, C. (2024). A Quantile Neural Network Framework for Two-stage Stochastic Optimization. arXiv preprint arXiv:2403.11707.

Work in progress