Transportation Science
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


TRANSPORTATION SCIENCE
Vol. 41, No. 4, November 2007, pp. 457-469
DOI: 10.1287/trsc.1060.0177
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Amaruchkul, K.
Right arrow Articles by Gupta, D.
Right arrow Search for Related Content

Single-Leg Air-Cargo Revenue Management

Kannapha Amaruchkul, William L. Cooper, Diwakar Gupta

Graduate Program in Industrial and Systems Engineering, Department of Mechanical Engineering, University of Minnesota
Graduate Program in Industrial and Systems Engineering, Department of Mechanical Engineering, University of Minnesota
Graduate Program in Industrial and Systems Engineering, Department of Mechanical Engineering, University of Minnesota

amar0017{at}umn.edu
billcoop{at}me.umn.edu
guptad{at}me.umn.edu

We consider a cargo booking problem on a single-leg flight with the goal of maximizing expected contribution. Each piece of cargo is endowed with a random volume and a random weight whose precise values are not known until just before the flight's departure. We formulate the problem as a Markov decision process (MDP). Exact solution of the formulation is impractical, because of its high-dimensional state space; therefore, we develop six heuristics. The first four heuristics are based on different value-function approximations derived from two computationally tractable MDPs, each with a one-dimensional state space. The remaining two heuristics are obtained from solving related methematical programming problems. We also compare the heuristics with the first-come, first-served (FCFS) policy. Simulation experiments suggest that the value function approximation derived from separate "volume" and "weight" problems offers the best approach. Comparisons of the expected contribution under the heuristic to an upper bound show that the heuristic is typically close to optimal.

Key Words: air-cargo operations; revenue management
History: Received: April 2005; revised: March 2006; accepted: August 2006.







HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Copyright © 2007 by INFORMS.