A Stochastic Integer Program with Dual Network Structure and Its Application to the Ground-Holding Problem

In this paper, we analyze a generalization of a classic network-flow model. The generalization involves the replacement of deterministic demand with stochastic demand. While this generalization destroys the original network structure, we show that the matrix underlying the stochastic model is dual n...

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Veröffentlicht in:Operations research Jg. 51; H. 1; S. 167 - 171
Hauptverfasser: Ball, Michael O, Hoffman, Robert, Odoni, Amedeo R, Rifkin, Ryan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Linthicum INFORMS 01.01.2003
Institute for Operations Research and the Management Sciences
Schlagworte:
Air traffic control
Airports
Analysis
Aviation
Collaboration
Commodities
Decision making
Flight time
Integer programming
Integers
Management science
Mathematical vectors
Modeling
Operations research
Programming integer: embedded networks
Stochastic models
Studies
Supply and demand
Technical Note
Traffic flow
Transportation
Transportation: air-traffic management
Vehicular flight
United States
ISSN:0030-364X, 1526-5463
Online-Zugang:Volltext
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Zusammenfassung:In this paper, we analyze a generalization of a classic network-flow model. The generalization involves the replacement of deterministic demand with stochastic demand. While this generalization destroys the original network structure, we show that the matrix underlying the stochastic model is dual network. Thus, the integer program associated with the stochastic model can be solved efficiently using network-flow or linear-programming techniques. We also develop an application of this model to the ground-holding problem in air-traffic management. The use of this model for the ground-holding problem improves upon prior models by allowing for easy integration into the newly developed ground-delay program procedures based on the Collaborative Decision-Making paradigm.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ISSN:0030-364X
1526-5463
DOI:10.1287/opre.51.1.167.12795