Real-time scheduling for distributed permutation flowshops with dynamic job arrivals using deep reinforcement learning-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Real-time scheduling for distributed permutation flowshops with dynamic job arrivals using deep reinforcement learning

Published:2022-10 Issue: Volume:54 Page:101776
ISSN:1474-0346
Container-title:Advanced Engineering Informatics
language:en
Short-container-title:Advanced Engineering Informatics

Author:

Yang Shengluo,Wang Junyi,Xu Zhigang

Funder

National Defense Basic Scientific Research Program of China

Ministry of National Defense of the People's Republic of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems,Building and Construction

Reference62 articles.

1. Permutation flow shop scheduling with multiple lines and demand plans using reinforcement learning;Brammer;Eur. J. Oper. Res.,2022

2. Production scheduling for blocking flowshop in distributed environment using effective heuristics and iterated greedy algorithm;Chen;Rob. Comput. Integr. Manuf.,2021

3. A competitive memetic algorithm for multi-objective distributed permutation flow shop scheduling problem;Deng;Swarm Evol. Comput.,2017

4. The distributed permutation flow shop to minimise the total flowtime;Fernandez-Viagas;Comput. Ind. Eng.,2018

5. A bounded-search iterated greedy algorithm for the distributed permutation flowshop scheduling problem;Fernandez-Viagas;Int. J. Prod. Res.,2014

Cited by 31 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. Multi-agent deep reinforcement learning for dynamic reconfigurable shop scheduling considering batch processing and worker cooperation;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. An incremental learning approach to dynamic parallel machine scheduling with sequence-dependent setups and machine eligibility restrictions;Applied Soft Computing;2024-10

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

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

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