Research on Refining the Distributed Supply Chain Procurement Plans Based on CRL

Author

Zhanguo, Xia ; Hongjie, Guan ; Ke, Wang

Author_Institution

Sch. of Comput. Sci. & Technol., China Univ. of Min. & Technol., Xuzhou

fYear

2008

fDate

23-25 May 2008

Firstpage

119

Lastpage

122

Abstract

In this paper, we propose a method of coordinated reinforcement learning (CRL) to refine the distributed transportation plans generated by a group of agents using double auction market mechanism (DAMM) in the context of supply chain procurement problem. Through analyzing the drawbacks of DAMM due to its strict market rules, we develop a refinement method based on reinforcement learning, namely CRL. Numerical results demonstrate that CRL effectively refines the distributed transportation plans generated by the DAMM.

Keywords

electronic commerce; learning (artificial intelligence); multi-agent systems; procurement; supply chain management; transportation; coordinated reinforcement learning method; distributed supply chain procurement plan; distributed transportation plan; double auction market mechanism; e-procurement problem; multiagent system; refinement method; Computer science; Costs; Information processing; Learning; Monitoring; Multiagent systems; Procurement; Software agents; Supply chains; Transportation;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Processing (ISIP), 2008 International Symposiums on

Conference_Location

Moscow

Print_ISBN

978-0-7695-3151-9

Type

conf

DOI

10.1109/ISIP.2008.53

Filename

4554069