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Cong Zhang (张聪)
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Year
Learning to dispatch for job shop scheduling via deep reinforcement learning
C Zhang, W Song, Z Cao, J Zhang, PS Tan, X Chi
Advances in Neural Information Processing Systems 33, 1621-1632, 2020
2472020
A review on learning to solve combinatorial optimisation problems in manufacturing
C Zhang, Y Wu, Y Ma, W Song, Z Le, Z Cao, J Zhang
IET Collaborative Intelligent Manufacturing 5 (1), e12072, 2023
142023
Learning to Solve Multiple-TSP with Time Window and Rejections via Deep Reinforcement Learning
R Zhang, C Zhang, Z Cao, W Song, PS Tan, J Zhang, B Wen, J Dauwels
IEEE Transactions on Intelligent Transportation Systems, 2022
132022
Evolution strategies-based optimized graph reinforcement learning for solving dynamic job shop scheduling problem
C Su, C Zhang, D Xia, B Han, C Wang, G Chen, L Xie
Applied Soft Computing 145, 110596, 2023
62023
Sampling efficient deep reinforcement learning through preference-guided stochastic exploration
W Huang, C Zhang, J Wu, X He, J Zhang, C Lv
IEEE Transactions on Neural Networks and Learning Systems, 2023
32023
Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem
C Zhang, Z Cao, Y Wu, W Song, J Sun
arXiv, https://arxiv.org/abs/2402.17606, 2024
2024
Aligning Crowd Feedback via Distributional Preference Reward Modeling
D Li, C Zhang, K Dong, D Derrick, Goh, Xin, R Tang, Y Liu
arXiv preprint arXiv:2402.09764, https://arxiv.org/abs/2402.09764, 2024
2024
Deep reinforcement learning guided improvement heuristic for job shop scheduling
C Zhang, Z Cao, W Song, Y Wu, J Zhang
International Conference on Learning Representations (ICLR), 2024
2024
Intelligent job shop scheduling via deep reinforcement learning over graphs
C Zhang
Nanyang Technological University, 2023
2023
Decision-making with Imaginary Opponent Models
J Sun, S Chen, C Zhang, J Zhang
arXiv preprint arXiv:2211.11940, 2022
2022
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Articles 1–10