Title: A dynamic programming approach for agent's bidding strategy in TAC-SCM game

Authors: Soheil Sibdari; Xiaoqin Shelley Zhang; Saban Singh

Addresses: Charlton College of Business, University of Massachusetts Dartmouth, North Dartmouth, MA 02747, USA ' Department of Computer and Information Sciences, University of Massachusetts Dartmouth, North Dartmouth, MA 02747, USA ' Department of Computer and Information Sciences, University of Massachusetts Dartmouth, North Dartmouth, MA 02747, USA

Abstract: Intelligent agents have been developed for a number of e-commerce applications including supply chain management. In trading agent competition for supply chain management (TAC SCM), several manufacturer agents compete in a reverse auction in order to sell assembled computers to customers. The manufacturer agent's tasks include acquiring supplies, selling products and managing its local manufacturing process. The agent decide whether to accept an arriving bid in order to maximise its long-term expected prot. In this paper, we use dynamic programming to provide a pricing strategy for the TAC SCM. We consider a competition between an individual manufacturer agent and other automated agents in TAC SCM. The experiment results show that this strategy improves the agent's revenue signicantly comparing to several other heuristics in the current practice. This approach can also be applied to similar bidding problems in other e-commerce applications.

Keywords: auction theory; supply chain management; SCM; dynamic programming; bid pricing; bidding strategy; intelligent agents; e-commerce; electronic commerce; multi-agent systems; agent-based systems; trading agent competition; reverse auctions; pricing strategy.

DOI: 10.1504/IJOR.2012.046644

International Journal of Operational Research, 2012 Vol.14 No.2, pp.121 - 134

Available online: 13 Apr 2012 *

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