Flexible Job Shop Scheduling Based on Deep Reinforcement Learning-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Flexible Job Shop Scheduling Based on Deep Reinforcement Learning

Published:2021-10-29 Issue: Volume: Page:
ISSN:
Container-title:2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT)
language:
Short-container-title:

Author:

Feng Yi¹,Zhang Lu¹,Yang Zhile²,Guo Yuanjun²,Yang Dongsheng³

Affiliation:

1. Dalian University of Technology,School of Control Science and Engineering,Dalian,China

2. Shenzhen Institute of Advanced Technology,Chinese Academy of Sciences,Shenzhen,China

3. Northeastern University,Intelligent Electrical Science and Technology Research Institute,Shenyang,China

Funder

Research and Development

Innovation Fund

Chinese Academy of Sciences

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9731095/9730887/09731322.pdf?arnumber=9731322

Reference14 articles.

1. Proximal policy optimization algorithms;schulman;arXiv preprint arXiv 1707 06347,2017

2. Flexible job-shop scheduling problem with resource recovery constraints

3. An effective multi-objective discrete virus optimization algorithm for flexible job-shop scheduling problem with controllable processing times

4. Asynchronous methods for deep reinforcement learning;mnih;International Conference on Machine Learning,2016

Cited by 13 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. Makine Çizelgeleme Problemlerinin Çözümünde Pekiştirmeli Öğrenme Etkisinin Analizi;ALKÜ Fen Bilimleri Dergisi;2024-08-30

2. Flexible job shop scheduling via deep reinforcement learning with meta-path-based heterogeneous graph neural network;Knowledge-Based Systems;2024-07

3. Dual Dynamic Attention Network for Flexible Job Scheduling with Reinforcement Learning;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

4. A novel collaborative agent reinforcement learning framework based on an attention mechanism and disjunctive graph embedding for flexible job shop scheduling problem;Journal of Manufacturing Systems;2024-06

5. Low-Carbon Flexible Job Shop Scheduling Problem Based on Deep Reinforcement Learning;Sustainability;2024-05-27

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3