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CMieux: adaptive strategies for competitive supply chain trading

Published: 13 August 2006 Publication History

Abstract

Supply chains are a central element of today's global economy. Existing 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. Each agent is responsible for running the procurement, planning and bidding operations of a PC assembly company, while competing with others for both customer orders and supplies under varying market conditions. 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.

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  • (2010)Supply Chain Management Sales Using XCSRLearning Classifier Systems10.1007/978-3-642-17508-4_10(145-165)Online publication date: 2010
  • (2010)Analyzing Market Interactions in a Multi-agent Supply Chain EnvironmentExploring the Grand Challenges for Next Generation E-Business10.1007/978-3-642-17449-0_5(44-58)Online publication date: 2010
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cover image ACM Other conferences
ICEC '06: Proceedings of the 8th international conference on Electronic commerce: The new e-commerce: innovations for conquering current barriers, obstacles and limitations to conducting successful business on the internet
August 2006
624 pages
ISBN:1595933921
DOI:10.1145/1151454
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 August 2006

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Author Tags

  1. TAC SCM
  2. multi-agent systems
  3. supply chain management
  4. trading agents

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ICEC '06 Paper Acceptance Rate 53 of 112 submissions, 47%;
Overall Acceptance Rate 150 of 244 submissions, 61%

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Cited By

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  • (2017)Agent Marketplaces and Deep Learning in Enterprises: The COMPOSITION Project2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC)10.1109/COMPSAC.2017.46(749-754)Online publication date: Jul-2017
  • (2010)Supply Chain Management Sales Using XCSRLearning Classifier Systems10.1007/978-3-642-17508-4_10(145-165)Online publication date: 2010
  • (2010)Analyzing Market Interactions in a Multi-agent Supply Chain EnvironmentExploring the Grand Challenges for Next Generation E-Business10.1007/978-3-642-17449-0_5(44-58)Online publication date: 2010
  • (2010)The 2007 TAC SCM Prediction ChallengeAgent-Mediated Electronic Commerce and Trading Agent Design and Analysis10.1007/978-3-642-15237-5_13(175-189)Online publication date: 2010
  • (2009)Forecasting market prices in a supply chain gameElectronic Commerce Research and Applications10.1016/j.elerap.2008.11.0058:2(63-77)Online publication date: 1-Mar-2009
  • (2009)Flexible decision control in an autonomous trading agentElectronic Commerce Research and Applications10.1016/j.elerap.2008.09.0048:2(91-105)Online publication date: 1-Mar-2009
  • (2008)Using Information Gain to Analyze and Fine Tune the Performance of Supply Chain Trading AgentsAgent-Mediated Electronic Commerce and Trading Agent Design and Analysis10.1007/978-3-540-88713-3_13(182-199)Online publication date: 2008
  • (2008)The CrocodileAgentProceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence10.1007/978-3-540-69052-8_90(865-875)Online publication date: 18-Jun-2008
  • (2007)Forecasting market prices in a supply chain gameProceedings of the 6th international joint conference on Autonomous agents and multiagent systems10.1145/1329125.1329408(1-8)Online publication date: 14-May-2007
  • (2007)The CrocodileAgentProceedings of the 1st KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications10.1007/978-3-540-72830-6_62(597-606)Online publication date: 31-May-2007
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