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CMieux: adaptive strategies for competitive supply chain trading

Published: 01 June 2006 Publication History

Abstract

Existing supply chain management practices consist primarily of static interactions between established partners. Global competition, shorter product life cycles and the emergence of Internet-mediated business solutions create an incentive for exploring more dynamic supply chain practices. The Supply Chain Trading Agent Competition (TAC SCM) was designed to explore approaches to dynamic supply chain trading. TAC SCM pits against one another trading agents developed by teams from around the world. This paper presents Carnegie Mellon University's 2005 TAC SCM entry, the CMieux supply chain trading agent. CMieux implements a novel approach to coordinating supply chain bidding, procurement and planning, with an emphasis on the ability to rapidly adapt to changing market conditions. We present empirical results based on 200 games involving agents entered by 25 different teams during what can be seen as the most competitive phase of the 2005 tournament. Not only did CMieux perform among the top five agents, it significantly outperformed these agents in procurement while matching their bidding performance.

References

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BENISCH, M., GREENWALD, A., GRYPARI, I., LEDERMAN, R., NARODITSKY, V., AND TSCHANTZ, M. 2004. Botticelli: A supply chain management agent. In Third International Joint Conference on Autonomous Agents and Multi-Agent Systems.
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BENISH, M., SARDINHA, A., ANDREWS, J., AND SADEH, N. Cmieux 2005: Design and analysis of carnegie mellon universitys entry in the supply chain trading agent competition. Tech. rep.
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CHOPRA, S. AND MEINDL, P. 2004. Supply Chain Management. Pearson Prentice Hall, New Jersey.
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  • (2022)Trading AgentsundefinedOnline publication date: 11-Mar-2022
  • (2011)Contracts Negotiation in Market Environments Taking into Consideration the Strength of Each Economic PlayerAdvances on Practical Applications of Agents and Multiagent Systems10.1007/978-3-642-19875-5_38(299-308)Online publication date: 2011
  • (2010)Towards a dynamic model of supply chain regimes for complex multi-agent markets2010 IEEE International Conference on Systems, Man and Cybernetics10.1109/ICSMC.2010.5642406(3219-3225)Online publication date: Oct-2010
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Published In

cover image ACM SIGecom Exchanges
ACM SIGecom Exchanges  Volume 6, Issue 1
June 2006
44 pages
EISSN:1551-9031
DOI:10.1145/1150735
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 June 2006
Published in SIGECOM Volume 6, Issue 1

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Author Tags

  1. TAC SCM
  2. supply chain management
  3. trading agents

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Cited By

View all
  • (2022)Trading AgentsundefinedOnline publication date: 11-Mar-2022
  • (2011)Contracts Negotiation in Market Environments Taking into Consideration the Strength of Each Economic PlayerAdvances on Practical Applications of Agents and Multiagent Systems10.1007/978-3-642-19875-5_38(299-308)Online publication date: 2011
  • (2010)Towards a dynamic model of supply chain regimes for complex multi-agent markets2010 IEEE International Conference on Systems, Man and Cybernetics10.1109/ICSMC.2010.5642406(3219-3225)Online publication date: Oct-2010
  • (2010)A Demand-Driven Approach for a Multi-Agent System in Supply Chain ManagementAgent-Mediated Electronic Commerce. Designing Trading Strategies and Mechanisms for Electronic Markets10.1007/978-3-642-15117-0_7(88-101)Online publication date: 2010
  • (2009)Product pricing using adaptive real-time probability of acceptance estimations based on economic regimesProceedings of the 11th International Conference on Electronic Commerce10.1145/1593254.1593281(176-185)Online publication date: 12-Aug-2009
  • (2008)Adaptive strategies for predicting bidding prices in supply chain managementProceedings of the 10th international conference on Electronic commerce10.1145/1409540.1409548(1-10)Online publication date: 19-Aug-2008
  • (2008)Deploying Neural-Network-Based Models for Dynamic Pricing in Supply Chain ManagementProceedings of the 2008 International Conference on Computational Intelligence for Modelling Control & Automation10.1109/CIMCA.2008.92(680-685)Online publication date: 10-Dec-2008

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