Robbert Reijnen

14 papers A* 2A 1Journal 7Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Deep Reinforcement Learning Based Genetic Framework for Flexible Job-Shop Scheduling Under Practical Constraints. LION (1) Kjell van Straaten, Robbert Reijnen, Zaharah Bukhsh, Yaoxin Wu, Yingqian Zhang
2025	J	`jnl`	Graph neural networks for job shop scheduling problems: A survey. Comput. Oper. Res. Igor G. Smit, Jianan Zhou, Robbert Reijnen, Yaoxin Wu, Jian Chen, Cong Zhang, Zaharah Bukhsh, Yingqian Zhang, Wim Nuijten
2025	A*	`conf`	Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization. ICML Robbert Reijnen, Yaoxin Wu, Zaharah Bukhsh, Yingqian Zhang
2025	J	`jnl`	Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization. CoRR Robbert Reijnen, Yaoxin Wu, Zaharah Bukhsh, Yingqian Zhang
2025	A	`conf`	Search Trajectory Network-Enhanced Multi-Objective Dynamic Algorithm Configuration. ECAI Robbert Reijnen, Zaharah Bukhsh, Hoong Chuin Lau, Yaoxin Wu, Yingqian Zhang
2024	J	`jnl`	Graph Neural Networks for Job Shop Scheduling Problems: A Survey. CoRR Igor G. Smit, Jianan Zhou, Robbert Reijnen, Yaoxin Wu, Jian Chen, Cong Zhang, Zaharah Bukhsh, Wim Nuijten, Yingqian Zhang
2024	A*	`conf`	Online Control of Adaptive Large Neighborhood Search Using Deep Reinforcement Learning. ICAPS Robbert Reijnen, Yingqian Zhang, Hoong Chuin Lau, Zaharah Allah Bukhsh
2023	J	`jnl`	Job Shop Scheduling Benchmark: Environments and Instances for Learning and Non-learning Methods. CoRR Robbert Reijnen, Kjell van Straaten, Zaharah Allah Bukhsh, Yingqian Zhang
2023	—	`conf`	Learning to Adapt Genetic Algorithms for Multi-Objective Flexible Job Shop Scheduling Problems. GECCO Companion Robbert Reijnen, Yingqian Zhang, Zaharah Allah Bukhsh, Mateusz Guzek
2023	J	`jnl`	The first AI4TSP competition: Learning to solve stochastic routing problems. Artif. Intell. Yingqian Zhang, Laurens Bliek, Paulo da Costa, Reza Refaei Afshar, Robbert Reijnen, Tom Catshoek, Daniël Vos, Sicco Verwer, Fynn Schmitt-Ulms, André Hottung, Tapan Shah, Meinolf Sellmann, Kevin Tierney, Carl Perreault-Lafleur, Caroline Leboeuf, Federico Bobbio, Justine Pepin, Warley Almeida Silva, Ricardo Gama, Hugo L. Fernandes, Martin Zaefferer, Manuel López-Ibáñez, Ekhine Irurozki
2022	—	`conf`	Deep Reinforcement Learning for Adaptive Parameter Control in Differential Evolution for Multi-Objective Optimization. SSCI Robbert Reijnen, Yingqian Zhang, Zaharah Allah Bukhsh, Mateusz Guzek
2022	J	`jnl`	Learning Adaptive Evolutionary Computation for Solving Multi-Objective Optimization Problems. CoRR Remco Coppens, Robbert Reijnen, Yingqian Zhang, Laurens Bliek, Berend Steenhuisen
2022	J	`jnl`	Operator Selection in Adaptive Large Neighborhood Search using Deep Reinforcement Learning. CoRR Robbert Reijnen, Yingqian Zhang, Hoong Chuin Lau, Zaharah Allah Bukhsh
2020	—	`conf`	Combining Deep Reinforcement Learning with Search Heuristics for Solving Multi-Agent Path Finding in Segment-based Layouts. SSCI Robbert Reijnen, Yingqian Zhang, Wim Nuijten, Çaglar Senaras, Mariana Goldak-Altgassen