A Reinforcement Learning Approach to Dynamic Scheduling in a Product-Mix Flexibility Environment

A Reinforcement Learning Approach to Dynamic Scheduling in a Product-Mix Flexibility Environment

Machine bottlenecks, resulting from shifting and unbalanced machine loads caused by resource capacity limitations, impair product-mix flexibility production systems. Thus, the knowledge base (KB) of a dynamic scheduling control system should be dynamic and include a knowledge revision mechanism for...

Full description

Bibliographic Details
Main Authors: Yeou-Ren Shiue, Ken-Chuan Lee, Chao-Ton Su
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Manufacturing execution system
dynamic scheduling
machine learning
reinforcement learning
Q-learning
Online Access:https://ieeexplore.ieee.org/document/9110908/

Internet

https://ieeexplore.ieee.org/document/9110908/

Similar Items