Botticelli: a supply chain management agent designed to optimize under uncertainty

Authors:
Michael Benisch;Amy Greenwald;Ioanna Grypari;Roger Lederman;Victor Naroditskiy;Michael Tschantz
Affiliations:
Brown University, Providence, RI;Brown University, Providence, RI;Brown University, Providence, RI;Brown University, Providence, RI;Brown University, Providence, RI;Brown University, Providence, RI
Venue:
ACM SIGecom Exchanges
Year:
2004

Citing 3
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Abstract

The paper describes the design of the agent BOTTICELLI, a finalist in the 2003 Trading Agent Competition in Supply Chain Management (TAC SCM). In TAC SCM, a simulated computer manufacturing scenario, BOTTICELLI competes with other agents to win customer orders and negotiates with suppliers to procure the components necessary to complete its orders. We formalize subproblems that dictate BOTTICELLI's behavior. Stochastic programming approaches to bidding and scheduling are developed in attempt to solve these problems optimally. In addition, we describe greedy methods that yield useful approximations. Test results compare the performance and computational effciency of these two techniques.