Network Cargo Capacity Management

Tatsiana Levina (), Yuri Levin (), Jeff McGill () and Mikhail Nediak ()
Additional contact information
Tatsiana Levina: School of Business, Queen's University, Kingston, Ontario K7L 3N6, Canada
Yuri Levin: School of Business, Queen's University, Kingston, Ontario K7L 3N6, Canada
Jeff McGill: School of Business, Queen's University, Kingston, Ontario K7L 3N6, Canada
Mikhail Nediak: School of Business, Queen's University, Kingston, Ontario K7L 3N6, Canada

Operations Research, 2011, vol. 59, issue 4, 1008-1023

Abstract: We consider the problem faced by an airline that is flying both passengers and cargo over a network of locations on a fixed periodic schedule. Bookings for many classes of cargo shipments between origin-destination pairs in this network are made in advance, but the weight and volume of aircraft capacity available for cargo as well as the exact weight and volume of each shipment are not known at the time of booking. The problem is to control cargo accept/reject decisions to maximize expected profits while ensuring effective dispatch of accepted shipments through the network. This network stochastic dynamic control problem has very high computational complexity. We propose a linear programming and stochastic simulation-based computational method for learning approximate control policies and discuss their structural properties. The proposed method is flexible and can utilize historical booking data as well as decisions generated by default control policies.

Keywords: transportation; freight; dynamic programming; applications (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
http://dx.doi.org/10.1287/opre.1110.0929 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:59:y:2011:i:4:p:1008-1023

Access Statistics for this article

More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().