Reviving integer programming approaches for AI planning: A branch-and-cut framework

Menkes Van Den Briel, Thomas Vossen, Subbarao Kambhampati

Research output: Chapter in Book/Report/Conference proceedingConference contribution

28 Scopus citations

Abstract

The conventional wisdom in the planning community is that planners based on integer programming (IP) techniques cannot compete with satisfiability and constraint satisfaction based planners. In this paper we challenge this perception of IP techniques by presenting novel formulations that outperform the most efficient SAT-based planner that currently exists. We will present a series of IP formulations that (1) use multivalued state variables that are represented by networks, and that (2) control the encoding length by progressively generalizing the notion of parallelism. The resulting IP encodings are solved within a branch-and- cut framework and yield impressive results.

Original languageEnglish (US)
Title of host publicationICAPS 2005 - Proceedings of the 15th International Conference on Automated Planning and Scheduling
Pages310-319
Number of pages10
StatePublished - Dec 1 2005
Event15th International Conference on Automated Planning and Scheduling, ICAPS 2005 - Monterey, CA, United States
Duration: Jun 5 2005Jun 10 2005

Publication series

NameICAPS 2005 - Proceedings of the 15th International Conference on Automated Planning and Scheduling

Other

Other15th International Conference on Automated Planning and Scheduling, ICAPS 2005
CountryUnited States
CityMonterey, CA
Period6/5/056/10/05

ASJC Scopus subject areas

  • Information Systems and Management

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    Van Den Briel, M., Vossen, T., & Kambhampati, S. (2005). Reviving integer programming approaches for AI planning: A branch-and-cut framework. In ICAPS 2005 - Proceedings of the 15th International Conference on Automated Planning and Scheduling (pp. 310-319). (ICAPS 2005 - Proceedings of the 15th International Conference on Automated Planning and Scheduling).