All regular talks are 15 minutes + 5 Min Q&A. 

19 September (14:00-18:00)

14:00 - 14:05: Opening

14:05-15:05 Session 1 

• LLMs can schedule, by Henrik Abgaryan (PSL DAUPHINE); Tristan Cazenave (PSL DAUPHINE ); Ararat Harutyunyan (PSL DAUPHINE )

• Simulating classification models to evaluate Predict-Then-Optimize methods, by Pieter Smet (KU Leuven)

• Hyperparameter and Neural Architecture Search via Evolutionary Optimization for Reinforcement Learning: HPNAS-RL, by Nihal Acharya Adde (Volkswagen AG); Hanno Gottschalk (TU-Berlin)

15:05 - 16:00 Keynote Speech:  Towards Foundation Models for Solving Vehicle Routing Problems, by Zhiguang Cao (Singapore Management University, Singapore)

16:00 - 16:30 Coffee Break

16:30-17:50 Session 2: 

• Offline Reinforcement Learning for Scheduling: Learning from Limited and Sub-Optimal Data, Jesse van Remmerden (TU Eindhoven); Zaharah Bukhsh (TU Eindhoven); Yingqian Zhang (TU Eindhoven)

• On the Impact of Weight Discretization in QUBO-Based SVM Training, Sascha Mücke (TU Dortmund)

• A Clustering-based Variable Ordering Framework for Relaxed Decision Diagrams, Mohsen Nafar (Bielefeld University); Hamed Azami Zenouzagh (Gran Sasso Science Institute (GSSI)); Michael Römer (Bielefeld University); Lin Xie (Brandenburg University of Technology)

• A Unified Neural Solver for Vehicle Routing Problems via Multi-Teacher Guided Knowledge Distillation, Suyu Liu (NTU); Zhiguang Cao (Singapore Management University); Lizi Liao (Singapore Management University); Yew-Soon Ong (Nanyang Technical University)

17:50 - 18:00 Closing