An Algorithm for Procurement in Supply Chain Management

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TypeArticle
ConferenceWorkshop on Trading Agent Design and Analysis (TADA'04); held inconjunction with the 3rd International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'04), July 20, 2004., New York, New York, USA
Subjectsupply-chain management; Markov decision process; dynamic programming; purchasing
AbstractWe propose a technique for use in supply-chain management that assists the decision-making process for purchases of direct goods. Based on projections for future prices and demand, RFQs are constructed and quotes are accepted that optimize the level of inventory each day, while minimizing total cost. The problem is modeled as a Markov decision process (MDP), which allows for the computation of the utility of actions to be based on the utilities of consequential future states. Dynamic programming is then used to determine the optimal quote requests and accepts at each state in the MDP. We also discuss the implementation of our entry in the TAC-SCM game, NaRC, and demonstrate how the general technique presented can be specialized for use in our TAC-SCM agent.
Publication date
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number47455
NPARC number5765022
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Record identifier3e4295e9-504c-4188-82dc-545dbafc9456
Record created2009-03-29
Record modified2016-05-09
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