A graph neural networks-based deep Q-learning approach for job shop scheduling problems in traffic management-Reference-Cited by-同舟云学术

A graph neural networks-based deep Q-learning approach for job shop scheduling problems in traffic management

Published:2022-08 Issue: Volume:607 Page:1211-1223
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Liu Zeyi,Wang Yuan,Liang Xingxing,Ma Yang,Feng Yanghe,Cheng Guangquan,Liu Zhong

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference28 articles.

1. The job-shop problem: Old and new challenges;Brucker,2007

2. A. Almeida, J. Macedo, J. Machado, Optimization of urban semaphore times turning into jssp (08 2018).

3. Terminal area green optimization using job-shop scheduling techniques;Bagassi;27th Congress of the International Council of the Aeronautical Sciences 2010, ICAS,2010

4. Scheduling models for air traffic control in terminal areas;Bianco;J. Sched.,2006

5. C. Mannino, L. Lamorgese, A noncompact formulation for job-shop scheduling problems in traffic management, Operations Research To appear (11 2018). doi:10.1287/opre.2018.1837.

Cited by 20 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 multi-level action coupling reinforcement learning approach for online two-stage flexible assembly flow shop scheduling;Journal of Manufacturing Systems;2024-10

2. Domain Knowledge Used in Meta-Heuristic Algorithms for the Job-Shop Scheduling Problem: Review and Analysis;Tsinghua Science and Technology;2024-10

3. Real-time scheduling for two-stage assembly flowshop with dynamic job arrivals by deep reinforcement learning;Advanced Engineering Informatics;2024-10

4. Graph Neural Network and Imaging Based Vehicle Classification for Traffic Monitoring System;Mathematical Models Using Artificial Intelligence for Surveillance Systems;2024-08-09

5. Dynamic Job-Shop Scheduling via Graph Attention Networks and Deep Reinforcement Learning;IEEE Transactions on Industrial Informatics;2024-06