Controlling a supply chain agent using value-based decomposition

ABSTRACT

We present and evaluate the design of Deep Maize, our entry in the 2005 Trading Agent Competition Supply Chain Management scenario. The central idea is to decompose the problem by estimating the value of key resources in the game. We first create a high-level production schedule that considers cross-cutting constraints and future decisions, but abstracts aways from the details of sales and purchasing. We then make specific sales and purchasing decisions separately, coordinating these decisions with the high-level schedule using resource values derived from the schedule. All of these decisions are made using approximate optimization techniques and make use of explicit predictions about market conditions. Deep Maize was one of the most successful agents in the 2005 tournament, both in overall performance and on specific measures that emphasize coordination.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.1 Applications and Expert Systems

General Terms:
Design, Experimentation

Keywords:
coordination, decomposition, optimization, scheduling, supply chain management, trading agents