An actor-critic framework based on deep reinforcement learning for addressing flexible job shop scheduling problems

An actor-critic framework based on deep reinforcement learning for addressing flexible job shop scheduling problems

With the rise of Industry 4.0, manufacturing is shifting towards customization and flexibility, presenting new challenges to meet rapidly evolving market and customer needs. To address these challenges, this paper suggests a novel approach to address flexible job shop scheduling problems (FJSPs) thr...

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Bibliographic Details
Main Authors: Cong Zhao, Na Deng
Format: Article
Language:English
Published: AIMS Press 2024-01-01
Series:Mathematical Biosciences and Engineering
Subjects:
flexible job shop scheduling problems
deep reinforcement learning
actor-critic method
markov decision process
deep neural networks
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2024062?viewType=HTML

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https://www.aimspress.com/article/doi/10.3934/mbe.2024062?viewType=HTML

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