A multi-action deep reinforcement learning framework for flexible Job-shop scheduling problem-Reference-Cited by-同舟云学术

A multi-action deep reinforcement learning framework for flexible Job-shop scheduling problem

Published:2022-11 Issue: Volume:205 Page:117796
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Lei Kun,Guo Peng,Zhao Wenchao,Wang Yi,Qian Linmao,Meng Xiangyin,Tang Liansheng

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference68 articles.

1. S. Amizadeh S. Matusevych M. Weimer Learning to solve circuit-SAT: An unsupervised differentiable approach In International Conference on Learning Representations 2018 URL.

2. Linguistic-based meta-heuristic optimization model for flexible job shop scheduling;Baykasoglu;International Journal of Production Research,2002

3. Test instances for the flexible job shop scheduling problem with work centers;Behnke;Research Report,2012

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

5. Parallel hybrid metaheuristics for the flexible job shop problem;Bożejko;Computers & Industrial Engineering,2010

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