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2020 – today
- 2024
[c4]Robbert Reijnen, Yingqian Zhang, Hoong Chuin Lau, Zaharah Allah Bukhsh:
Online Control of Adaptive Large Neighborhood Search Using Deep Reinforcement Learning. ICAPS 2024: 475-483- [i4]Igor G. Smit, Jianan Zhou, Robbert Reijnen, Yaoxin Wu, Jian Chen, Cong Zhang, Zaharah Bukhsh, Wim Nuijten, Yingqian Zhang
:
Graph Neural Networks for Job Shop Scheduling Problems: A Survey. CoRR abs/2406.14096 (2024) - 2023
- [j1]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:
The first AI4TSP competition: Learning to solve stochastic routing problems. Artif. Intell. 319: 103918 (2023) - [c3]Robbert Reijnen, Yingqian Zhang, Zaharah Allah Bukhsh, Mateusz Guzek:
Learning to Adapt Genetic Algorithms for Multi-Objective Flexible Job Shop Scheduling Problems. GECCO Companion 2023: 315-318 - [i3]Robbert Reijnen, Kjell van Straaten, Zaharah Allah Bukhsh, Yingqian Zhang:
Job Shop Scheduling Benchmark: Environments and Instances for Learning and Non-learning Methods. CoRR abs/2308.12794 (2023) - 2022
- [c2]Robbert Reijnen, Yingqian Zhang, Zaharah Allah Bukhsh, Mateusz Guzek:
Deep Reinforcement Learning for Adaptive Parameter Control in Differential Evolution for Multi-Objective Optimization. SSCI 2022: 804-811 - [i2]Robbert Reijnen, Yingqian Zhang, Hoong Chuin Lau, Zaharah Allah Bukhsh:
Operator Selection in Adaptive Large Neighborhood Search using Deep Reinforcement Learning. CoRR abs/2211.00759 (2022) - [i1]Remco Coppens, Robbert Reijnen, Yingqian Zhang, Laurens Bliek, Berend Steenhuisen:
Learning Adaptive Evolutionary Computation for Solving Multi-Objective Optimization Problems. CoRR abs/2211.09719 (2022) - 2020
- [c1]Robbert Reijnen, Yingqian Zhang, Wim Nuijten, Çaglar Senaras, Mariana Goldak-Altgassen:
Combining Deep Reinforcement Learning with Search Heuristics for Solving Multi-Agent Path Finding in Segment-based Layouts. SSCI 2020: 2647-2654
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