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Session MC-3: (Deep) Reinforcement Learning for Combinatorial Optimization 1 in stream Data Science Meets Optimization
Monday, 12:30-14:00Room: 1005 (building: 202)
| Session chair(s): |
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| 1566. PPSTOW: An End-to-End Deep Reinforcement Learning Model for Master Stowage Planning on Container Vessels |
Jaike van Twiller
[R] - Denmark | accepted | ||
| Djordje Grbic
[] - Denmark | ||||
| Rune Jensen
[R] - Denmark | ||||
| 1436. A Tale of Middle-Mile Logistics, Graph Neural Networks, and Reinforcement Learning |
Thibaut Cuvelier
[R] - France | accepted | ||
| Onno Eberhard
[] - Germany | ||||
| Bruno De Backer
[] - France | ||||
| 2381. Addressing Real-World Side Constraints in Combinatorial Optimization with Deep Reinforcement Learning |
Nayeli Gast Zepeda
[R] - Germany | accepted | ||
| Kevin Tierney
[R] - Germany | ||||
| André Hottung
[R] - Germany | ||||
| 1057. Learning Efficient and Fair Policies for Collaborative Human-Robot Order Picking |
Igor Smit
[R] - Netherlands | accepted | ||
| Zaharah Bukhsh
[] - Netherlands | ||||
| Yingqian Zhang
[R] - Netherlands | ||||