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An Online Reinforcement Learning Approach for Solving the Dynamic Flexible Job-Shop Scheduling Problem for Multiple Products and Constraints

  • Published:2021-12 Issue: Volume: Page:
  • ISSN:
  • Container-title:2021 International Conference on Computational Science and Computational Intelligence (CSCI)
  • language:
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Author:

Ali Said Nour El-Din1,Samaha Yassin2,Azab Eman3,Shihata Lamia A.4,Mashaly Maggie2

Affiliation:

1. German University in Cairo,Mechatronics Department,Cairo,Egypt

2. German University in Cairo,Networks Department,Cairo,Egypt

3. German University in Cairo,Electronics Departement,Cairo,Egypt

4. German University in Cairo,Production Departement,Cairo,Egypt

Funder

Information Technology Industry Development Agency

Publisher

IEEE

Reference21 articles.

1. The Complexity of Flowshop and Jobshop Scheduling

2. An improved Q-learning based rescheduling method for flexible job-shops with machine failures

3. Flow-shop Scheduling based on Reinforcement Learning Algorithm;stefan;Production Systems and Information Engineering,2003

4. Reinforcement Learning: An Introduction

5. Sequencing and Scheduling: An Introduction to the Mathematics of the Job-Shop;french,1982

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