Integration of deep reinforcement learning and multi-agent system for dynamic scheduling of re-entrant hybrid flow shop considering worker fatigue and skill levels-Reference-Cited by-同舟云学术

Integration of deep reinforcement learning and multi-agent system for dynamic scheduling of re-entrant hybrid flow shop considering worker fatigue and skill levels

Published:2023-12 Issue: Volume:84 Page:102605
ISSN:0736-5845
Container-title:Robotics and Computer-Integrated Manufacturing
language:en
Short-container-title:Robotics and Computer-Integrated Manufacturing

Author:

Liu Youshan,Fan Jiaxin,Zhao Linlin,Shen Weiming,Zhang Chunjiang

Funder

Ministry of Science and Technology of the People's Republic of China

National Key Research and Development Program of China

National Natural Science Foundation of China National Outstanding Youth Science Fund Project

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,General Mathematics,Software,Control and Systems Engineering

Reference48 articles.

1. Deep reinforcement learning for dynamic scheduling of a flexible job shop;Liu;Int. J. Prod. Res.,2022

2. An extension of two machine sequencing problem;Arthanary;Opsearch,1971

3. Computers and Intracdtability: A Guide to the Theory of NP-Completeness;Johnson,1979

4. A discrete whale swarm algorithm for hybrid flow-shop scheduling problem with limited buffers;Zhang;Robot. Comput. Integr. Manuf.,2021

5. A hybrid evolutionary algorithm using two solution representations for hybrid flow-shop scheduling problem;Fan;IEEE Trans. Cybern.,2021

Cited by 19 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. Out-of-order execution enabled deep reinforcement learning for dynamic additive manufacturing scheduling;Robotics and Computer-Integrated Manufacturing;2025-02

2. A multi-level action coupling reinforcement learning approach for online two-stage flexible assembly flow shop scheduling;Journal of Manufacturing Systems;2024-10

3. Deep reinforcement learning for dynamic distributed job shop scheduling problem with transfers;Expert Systems with Applications;2024-10

4. Dynamic scheduling of hybrid flow shop problem with uncertain process time and flexible maintenance using NeuroEvolution of Augmenting Topologies;IET Collaborative Intelligent Manufacturing;2024-09

5. An improved co-evolutionary memetic algorithm based on novel schedule type and unconditional feasibility for hybrid flow-shop scheduling problem;Computers & Industrial Engineering;2024-07