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End-to-end on-line rescheduling from Gantt chart images using deep reinforcement learning

  • Published:2021-11-26 Issue: Volume: Page:1-30
  • ISSN:0020-7543
  • Container-title:International Journal of Production Research
  • language:en
  • Short-container-title:International Journal of Production Research

Author:

Palombarini Jorge Andrés12ORCID,Martínez Ernesto Carlos3

Affiliation:

1. Centro de Investigaciones y Transferencia Villa María (CIT-VM, CONICET-UNVM), Villa María CP, Argentina

2. Departamento Ingeniería en Sistemas de Información (UTN FRVM), Villa María CP, Argentina

3. Instituto de Desarrollo y Diseño (INGAR, CONICET-UTN), Santa Fe, Argentina

Funder

National Scientific and Technical Research Council of Argentina

National Technological University of Argentina

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management

Cited by 17 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. Machine learning in smart production logistics: a review of technological capabilities;International Journal of Production Research;2024-07-22

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

3. Graph reinforcement learning for flexible job shop scheduling under industrial demand response: A production and energy nexus perspective;Computers & Industrial Engineering;2024-07

4. Research on Optimization of Maintenance Task Scheduling for Metro Systems Based on Resource Constraints;Transportation Research Record: Journal of the Transportation Research Board;2024-06-24

5. A Deep Reinforcement Learning-based Rescheduling Method for Flexible Job Shops under Machine Breakdowns;2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD);2024-05-08
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