Predictive Planning for Supply Chain Management

Supply chains are ubiquitous in the manufacturing of many complex products. Traditionally, supply chains have been created through the intricate interactions of human representatives of the various companies involved. However recent advances in planning, scheduling, and autonomous agent technologies have sparked an interest, both in academia and in industry, in automating the process. The Trading Agent Competition Supply Chain Management (TAC SCM) scenario provides a unique testbed for studying and prototyping supply chain management agents by providing a competitive environment in which independently created agents can be tested against each other over the course of many simulations. This paper presents the features of TAC SCM from a planning and scheduling perspective and introduces TacTex-05, the champion agent from the 2005 competition. TacTex-05 takes a predictive approach to its many planning and scheduling decisions by estimating future resource availability and constraints. This paper focuses on these aspects of the agent and isolates their impact with controlled empirical tests.