Optimizing Robotic Mobile Fulfillment Systems for Order Picking Based on Deep Reinforcement Learning

Optimizing Robotic Mobile Fulfillment Systems for Order Picking Based on Deep Reinforcement Learning

Robotic Mobile Fulfillment Systems (RMFSs) face challenges in handling large-scale orders and navigating complex environments, frequently encountering a series of intricate decision-making problems, such as order allocation, shelf selection, and robot scheduling. To address these challenges, this pa...

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Bibliographic Details
Main Authors: Zhenyi Zhu, Sai Wang, Tuantuan Wang
Format: Article
Language:English
Published: MDPI AG 2024-07-01
Series:Sensors
Subjects:
supply chain management
automatic warehousing system
deep reinforcement learning
order allocation and sequencing
robot collaborative scheduling
robotic mobile fulfillment systems
Online Access:https://www.mdpi.com/1424-8220/24/14/4713

Internet

https://www.mdpi.com/1424-8220/24/14/4713

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