Cmieux Adaptive strategies for competitive supply chain trading.pdfVIP

下载本文档

3
0
约3万字
约 10页
2017-04-09 发布于江苏
举报
版权申诉

Cmieux Adaptive strategies for competitive supply chain trading.pdf

1、有哪些信誉好的足球投注网站（book118）网站文档一经付费（服务费），不意味着购买了该文档的版权，仅供个人/单位学习、研究之用，不得用于商业用途，未经授权，严禁复制、发行、汇编、翻译或者网络传播等，侵权必究。。
2、本站所有内容均由合作方或网友上传，本站不对文档的完整性、权威性及其观点立场正确性做任何保证或承诺！文档内容仅供研究参考，付费前请自行鉴别。如您付费，意味着您自己接受本站规则且自行承担风险，本站不退款、不进行额外附加服务；查看《如何避免下载的几个坑》。如果您已付费下载过本站文档，您可以点击这里二次下载。
3、如文档侵犯商业秘密、侵犯著作权、侵犯人身权等，请点击“版权申诉”（推荐），也可以打举报电话：400-050-0827(电话支持时间：9:00-18:30)。
4、该文档为VIP文档，如果想要下载，成为VIP会员后，下载免费。
5、成为VIP后，下载本文档将扣除1次下载权益。下载后，不支持退款、换文档。如有疑问请联系我们。
6、成为VIP后，您将拥有八大权益，权益包括：VIP文档下载权益、阅读免打扰、文档格式转换、高级专利检索、专属身份标志、高级客服、多端互通、版权登记。
7、VIP文档为合作方或网友上传，每下载1次，网站将根据用户上传文档的质量评分、类型等，对文档贡献者给予高额补贴、流量扶持。如果你也想贡献VIP文档。上传文档

Cmieux Adaptive strategies for competitive supply chain trading

CMieux: Adaptive Strategies for Competitive Supply Chain Trading Michael Benisch, Alberto Sardinha, James Andrews and Norman Sadeh School of Computer Science, Carnegie Mellon University Existing supply chain management practices consist primarily of static interactions between es- tablished 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 coordinat- ing 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. Categories and Subject Descriptors: I.2.1 [Artificial Intelligence]: Applications and Expert Systems; I.6.0 [Simulations and Modelling]: General General Terms: Multi-agent Systems Additional Key Words and Phrases: Trading agents, Supply chain management, TAC SCM 1. INTRODUCTION Existing supply chain management practices consist primarily of static interactions between established partners [Chopra and Meindl 2004]. As the Internet helps mediate an increasing number of supply chain transactions, there is a growing interest in investigating the potential for exploring the benefits of more dynamic supply chain practices [Arunachalam and Sadeh 2005; Sadeh et al. 1999]. The Supply Chain Tr