A Dynamic Programming Model for Algorithm Design in Simultaneous Auctions
WELCOM '01 Proceedings of the Second International Workshop on Electronic Commerce
Agent-based service composition through simultaneous negotiation in forward and reverse auctions
Proceedings of the 4th ACM conference on Electronic commerce
The 2003 Supply Chain Management Trading Agent Competition
ICEC '04 Proceedings of the 6th international conference on Electronic commerce
Sequential auctions for the allocation of resources with complementarities
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Continuous value function approximation for sequential bidding policies
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Fuzzy adaptive agent for supply chain management
Web Intelligence and Agent Systems
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We 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, requests-for-quotes 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 The model is then used to formalize the subproblem of determining optimal request quantities, yielding a technique that is shown experimentally to outperform a standard technique from the literature The implementation of our entry in the Trading Agent Competition-Supply Chain Management game is also discussed.