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Paper Abstract and Keywords
Presentation 2025-02-19 09:20
MARL with Automated Negotiation for Reduction of Bullwhip Effect in Serial Supply Chain
Hajime Endo, Katsuhide Fujita (TUAT) AI2024-9
Abstract (in Japanese) (See Japanese page) 
(in English) In supply chain management (SCM), it is crucial to optimize and manage the flow of product supply across multiple interconnected companies while mitigating the bullwhip effect, where demand fluctuations amplify as they propagate upstream in the supply chain (SC). Existing research has applied multi-agent reinforcement learning methods, specifically Heterogeneous-Agent Proximal Policy Optimization (HAPPO), to inventory management in SC. This approach enables centralized training and decentralized execution of agents deployed at each company, making it a practical solution that considers inter-company information confidentiality.
To maintain this decentralized execution capability while further suppressing the bullwhip effect, this study proposes the introduction of automated negotiations between agents in SCM using HAPPO. Through evaluation experiments, we demonstrate that the proposed method incorporating automated negotiations reduces the bullwhip effect more effectively than existing methods and adapts to situations different from those encountered during training.
Keyword (in Japanese) (See Japanese page) 
(in English) Supply Chain Management / Bullwhip Effect / Multi-Agent Reinforcement Learning / Automated Negotiation / / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 377, AI2024-9, pp. 1-6, Feb. 2025.
Paper # AI2024-9 
Date of Issue 2025-02-12 (AI) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF AI2024-9

Conference Information
Committee AI  
Conference Date 2025-02-19 - 2025-02-19 
Place (in Japanese) (See Japanese page) 
Place (in English) Nagoya Institute of Technology 
Topics (in Japanese) (See Japanese page) 
Topics (in English) SMASH25 Winter Symposium 
Paper Information
Registration To AI 
Conference Code 2025-02-AI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) MARL with Automated Negotiation for Reduction of Bullwhip Effect in Serial Supply Chain 
Sub Title (in English)  
Keyword(1) Supply Chain Management  
Keyword(2) Bullwhip Effect  
Keyword(3) Multi-Agent Reinforcement Learning  
Keyword(4) Automated Negotiation  
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1st Author's Name Hajime Endo  
1st Author's Affiliation Tokyo University of Agriculture and Technology (TUAT)
2nd Author's Name Katsuhide Fujita  
2nd Author's Affiliation Tokyo University of Agriculture and Technology (TUAT)
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Speaker Author-1 
Date Time 2025-02-19 09:20:00 
Presentation Time 20 minutes 
Registration for AI 
Paper # AI2024-9 
Volume (vol) vol.124 
Number (no) no.377 
Page pp.1-6 
#Pages 6 
Date of Issue 2025-02-12 (AI) 

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