Single-Site Perishable Inventory Management Under Uncertainties: A Deep Reinforcement Learning Approach
Author:
Affiliation:
1. School of Computer Science and Engineering, Nanyang Technological University, Singapore
2. Singapore Institute of Manufacturing Technology, Singapore
Funder
Ministry of Education - Singapore
A*STAR Cyber-Physical Production System
Model Factory@SIMTech
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computational Theory and Mathematics,Computer Science Applications,Information Systems
Link
http://xplorestaging.ieee.org/ielx7/69/10251471/10056278.pdf?arnumber=10056278
Reference27 articles.
1. Deep Reinforcement Learning Approach for Capacitated Supply Chain optimization under Demand Uncertainty
2. Capacitated lot sizing problems with inventory bounds
3. Reinforcement learning for supply chain optimization;kemmer;Proc of European Workshop on Reinforcement Learning,2018
4. A genetic algorithm approach for multi-product multi-period continuous review inventory models
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1. An application of deep reinforcement learning and vendor-managed inventory in perishable supply chain management;Engineering Applications of Artificial Intelligence;2024-01
2. Research on Food Dynamic Pricing Algorithm Based on Deep Reinforcement Learning;Lecture Notes in Electrical Engineering;2024
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