UTCS Artificial Intelligence
courses
talks/events
demos
people
projects
publications
software/data
labs
areas
admin
Predictive Planning for Supply Chain Management (2006)
David Pardoe
and
Peter Stone
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-2005, the champion agent from the 2005 competition. TacTex-2005 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.
View:
PDF
,
PS
,
HTML
Citation:
In
Proceedings of the International Conference on Automated Planning and Scheduling
, June 2006.
Bibtex:
@InProceedings{ICAPS06, title={Predictive Planning for Supply Chain Management}, author={David Pardoe and Peter Stone}, booktitle={Proceedings of the International Conference on Automated Planning and Scheduling}, month={June}, url="http://www.cs.utexas.edu/users/ai-lab?ICAPS06", year={2006} }
People
David Pardoe
Ph.D. Alumni
dpardoe [at] cs utexas edu
Peter Stone
Faculty
pstone [at] cs utexas edu
Areas of Interest
Other Areas
Planning
Supply Chain Management for Trading Agents
Labs
Learning Agents