The Robotics Institute
Search the site
RI | Publications | Continuous Management of Airlift and Tanker Resources: A Constraint-Based Approach

Text only version of this site

Continuous Management of Airlift and Tanker Resources: A Constraint-Based Approach
S. Smith, M. Becker, and L. Kramer
Mathematical and Computer Modeling -- Special Issue on Defense Transportation: Algorithms, Models and Applications for the 21st Centry, Vol. 39, No. 6-8, 2004, pp. 581-598.

Jump to: Download | Abstract | Notes | Text Reference | BibTeX Reference

Download [Help]

Adobe portable document format (pdf) [179 KB]

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract

Efficient allocation of aircraft and aircrews to transportation missions is an important priority at the USAF Air Mobility Command (AMC), where airlift demand must increasingly be met with less capacity and at lower cost. In addition to presenting a formidable optimization problem, the AMC resource management problem is complicated by the fact that it is situated in a continuously executing environment. Mission requests are received (and must be acted upon) incrementally, and, once allocation decisions have been communicated to the executing agents, subsequent opportunities for optimizing resource usage must be balanced against the cost of solution change. In this paper, we describe the technical approach taken to this problem in the AMC Barrel Allocator, a scheduling tool developed to address this problem and provide support for day-to-day allocation and management of AMC resources. The system utilizes incremental and configurable constraint-based search procedures to provide a range of automated and semi-automated scheduling capabilities. Most basically, the system provides an efficient solution to the fleet scheduling problem. More importantly to continuous operations, it also provides techniques for selectively re-optimizing to accommodate higher priority missions while minimizing disruption to most previously scheduled missions, and for selectively ``merging" previously planned missions to minimize non-productive flying time. In situations where all mission requirements cannot be met, the system can generate and compare alternative constraint relaxation options. The Barrel Allocator technology is currently transitioning into operational use within AMC's Tanker/Airlift Control Center (TACC). A version of the Barrel Allocator supporting airlift allocation was first incorporated as an experimental module of the AMC's Consolidated Air Mobility Planning System (CAMPS) in September 2000. In May 2003, a new tanker allocation module is scheduled for initial operational release to users as part of CAMPS Release 5.4.

Notes

Associated center: CIMDS
Associated lab/group: Intelligent Coordination and Logistics Laboratory
Associated project: AMC Barrelmaster Scheduling

Number of pages: 24

Text Reference

S. Smith, M. Becker, and L. Kramer, "Continuous Management of Airlift and Tanker Resources: A Constraint-Based Approach," Mathematical and Computer Modeling -- Special Issue on Defense Transportation: Algorithms, Models and Applications for the 21st Centry, Vol. 39, No. 6-8, 2004, pp. 581-598.

BibTeX Reference

@article{Smith_2004_4933,
   author = "Stephen Smith and Marcel Becker and Laurence Kramer",
   title = "Continuous Management of Airlift and Tanker Resources: A Constraint-Based Approach",
   journal = "Mathematical and Computer Modeling -- Special Issue on Defense Transportation: Algorithms, Models and Applications for the 21st Centry",
   year = "2004",
   volume = "39",
   number = "6-8",
   pages = "581-598"
}


The Robotics Institute is part of the School of Computer Science, Carnegie Mellon University.
For updates and comments, please see these instructions.
This page maintained by robotwebmaster@ri.cmu.edu