Permutation flow shop scheduling with multiple lines and demand plans using reinforcement learning

Author:

Brammer JanisORCID,Lutz Bernhard,Neumann Dirk

Publisher

Elsevier BV

Subject

Information Systems and Management,Management Science and Operations Research,Modeling and Simulation,General Computer Science,Industrial and Manufacturing Engineering

Reference30 articles.

1. Improvement heuristic for the flow-shop scheduling problem: An adaptive-learning approach;Agarwal;European Journal of Operational Research,2006

2. Mixed integer linear programming models for flow shop scheduling with a demand plan of job types;Bautista;Central European Journal of Operations Research,2018

3. Bello, I., Pham, H., Le, Q. V., Norouzi, M., & Bengio, S. (2016). Neural combinatorial optimization with reinforcement learning. Available at https://arxiv.org/abs/1611.09940, last accessed April 16, 2021.

4. Machine learning for combinatorial optimization: A methodological tour d’Horizon;Bengio;European Journal of Operational Research,2021

5. Brammer, J., Lutz, B., & Neumann, D. (2021). Permutation flow shop dataset. Mendeley Data, V3. https://data.mendeley.com/datasets/5txxwj2g6b/3.

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