Robbert Reijnen

According to our database, Robbert Reijnen authored at least 13 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

When does learning pay off? A study on DRL-based dynamic algorithm configuration for carbon-aware scheduling.

Andrea Mencaroni, Robbert Reijnen, Yingqian Zhang, Dieter Claeys

CoRR, April, 2026

2025

Graph neural networks for job shop scheduling problems: A survey.

Igor G. Smit, Jianan Zhou, Robbert Reijnen, Yaoxin Wu, Jian Chen, Cong Zhang, Zaharah Bukhsh, Yingqian Zhang, Wim Nuijten

Comput. Oper. Res., 2025

Deep Reinforcement Learning Based Genetic Framework for Flexible Job-Shop Scheduling Under Practical Constraints.

Kjell van Straaten, Robbert Reijnen, Zaharah Bukhsh, Yaoxin Wu, Yingqian Zhang

Proceedings of the Learning and Intelligent Optimization - 19th International Conference, 2025

Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization.

Robbert Reijnen, Yaoxin Wu, Zaharah Bukhsh, Yingqian Zhang

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Search Trajectory Network-Enhanced Multi-Objective Dynamic Algorithm Configuration.

Robbert Reijnen, Zaharah Bukhsh, Hoong Chuin Lau, Yaoxin Wu, Yingqian Zhang

Proceedings of the ECAI 2025 - 28th European Conference on Artificial Intelligence, 25-30 October 2025, Bologna, Italy, 2025

2024

Online Control of Adaptive Large Neighborhood Search Using Deep Reinforcement Learning.

Robbert Reijnen, Yingqian Zhang, Hoong Chuin Lau, Zaharah Allah Bukhsh

Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling, 2024

2023

The first AI4TSP competition: Learning to solve stochastic routing problems.

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

Artif. Intell., June, 2023

Job Shop Scheduling Benchmark: Environments and Instances for Learning and Non-learning Methods.

Robbert Reijnen, Kjell van Straaten, Zaharah Allah Bukhsh, Yingqian Zhang

CoRR, 2023

Learning to Adapt Genetic Algorithms for Multi-Objective Flexible Job Shop Scheduling Problems.

Robbert Reijnen, Yingqian Zhang, Zaharah Allah Bukhsh, Mateusz Guzek

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

2022

Learning Adaptive Evolutionary Computation for Solving Multi-Objective Optimization Problems.

Remco Coppens, Robbert Reijnen, Yingqian Zhang, Laurens Bliek, Berend Steenhuisen

CoRR, 2022

Operator Selection in Adaptive Large Neighborhood Search using Deep Reinforcement Learning.

Robbert Reijnen, Yingqian Zhang, Hoong Chuin Lau, Zaharah Allah Bukhsh

CoRR, 2022

Deep Reinforcement Learning for Adaptive Parameter Control in Differential Evolution for Multi-Objective Optimization.

Robbert Reijnen, Yingqian Zhang, Zaharah Allah Bukhsh, Mateusz Guzek

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

2020

Combining Deep Reinforcement Learning with Search Heuristics for Solving Multi-Agent Path Finding in Segment-based Layouts.

Robbert Reijnen, Yingqian Zhang, Wim Nuijten, Çaglar Senaras, Mariana Goldak-Altgassen

Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020