Smit, I. G., Wu, Y., Troubil, P., Zhang, Y., & Nuijten, W. P. M. (2025). Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling Problems. In T. Walsh, J. Shah, & Z. Kolter (Eds.), Proceedings of the 39th Annual AAAI Conference on Artificial Intelligence: AAAI-25 Technical Tracks 25 (pp. 26678-26687). (Proceedings of the AAAI Conference Read More …
Smit, I. G., Zhou, J., Reijnen, R., Wu, Y., Chen, J., Zhang, C., Bukhsh, Z., Zhang, Y. & Nuijten, W. P. M. (2025). Graph Neural Networks for Job Shop Scheduling Problems: A Survey. Computers and Operations Research, 176, Article 106914. https://doi.org/10.1016/j.cor.2024.106914 Abstract Job shop scheduling problems (JSSPs) represent a critical and challenging class of combinatorial Read More …
Igor Smit obtained his dual MSc. degree in Data Science in Engineering and Operations Management & Logistics cum laude at the Departments of Mathematics & Computer Science and Industrial Engineering & Innovation Sciences at Eindhoven University of Technology (Netherlands). His MSc. dissertation “Learning to Be Efficient and Fair for Collaborative Order Picking” was carried out Read More …
