Towards Standardising Reinforcement Learning Approaches for Production Scheduling Problems-Reference-Cited by-同舟云学术

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Towards Standardising Reinforcement Learning Approaches for Production Scheduling Problems

Published:2022 Issue: Volume:107 Page:1112-1119
ISSN:2212-8271
Container-title:Procedia CIRP
language:en
Short-container-title:Procedia CIRP

Author:

Rinciog Alexandru,Meyer Anne

Publisher

Elsevier BV

Subject

General Medicine

Reference62 articles.

1. Optimization of global production scheduling with deep reinforcement learning;Waschneck;Procedia CIRP,2018

2. Job shop scheduling by local search;Vaessens;Informs Journal on computing,1996

3. "cherry picking”: Writing from thin data;Morse;Qualitative health research,2010

4. Reinforcement learning applications to machine scheduling problems: a comprehensive literature review;Kayhan;Journal of Intelligent Manufacturing,2021

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Review on Reinforcement Learning in Production Scheduling: An Inferential Perspective;Algorithms;2024-08-07

2. A blueprint description of production scheduling models using asset administration shells;Production & Manufacturing Research;2024-03-11

3. Towards practicality: Navigating challenges in designing predictive-reactive scheduling;Procedia CIRP;2024

4. Reinforcement learning approach for multi-agent flexible scheduling problems;Journal of Physics: Conference Series;2023-09-01

5. A review on learning to solve combinatorial optimisation problems in manufacturing;IET Collaborative Intelligent Manufacturing;2023-03

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