A spatial pyramid pooling-based deep reinforcement learning model for dynamic job-shop scheduling problem-Reference-Cited by-同舟云学术

A spatial pyramid pooling-based deep reinforcement learning model for dynamic job-shop scheduling problem

Published:2023-12 Issue: Volume:160 Page:106401
ISSN:0305-0548
Container-title:Computers & Operations Research
language:en
Short-container-title:Computers & Operations Research

Author:

Wu Xinquan,Yan Xuefeng^ORCID

Publisher

Elsevier BV

Subject

Management Science and Operations Research,Modeling and Simulation,General Computer Science

Reference65 articles.

1. The shifting bottleneck procedure for job shop scheduling;Adams;Manage. Sci.,1988

2. A computational study of the job-shop scheduling problem;Applegate;Orsa J. Comput.,1991

3. A parallel artificial bee colony algorithm for the job shop scheduling problem with a dynamic migration strategy;Asadzadeh;Comput. Ind. Eng.,2016

4. Dynamic job-shop scheduling using reinforcement learning agents;Aydin;Robot. Auton. Syst.,2000

5. Bahdanau, Dzmitry, Cho, KyungHyun, Bengio, Yoshua, 2015. Neural machine translation by jointly learning to align and translate. In: 3rd International Conference on Learning Representations. ICLR.

Cited by 4 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. Two-stage double deep Q-network algorithm considering external non-dominant set for multi-objective dynamic flexible job shop scheduling problems;Swarm and Evolutionary Computation;2024-10

2. Design patterns of deep reinforcement learning models for job shop scheduling problems;Journal of Intelligent Manufacturing;2024-07-20

3. Knowledge-Based Effective Dispatch for Job Shop Scheduling;Journal of Circuits, Systems and Computers;2024-04-25

4. Dynamic job-shop scheduling using graph reinforcement learning with auxiliary strategy;Journal of Manufacturing Systems;2024-04