Aircraft and crew scheduling for fractional ownership programs.

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Bibliographic Details
Title:	Aircraft and crew scheduling for fractional ownership programs.
Authors:	Wei Yang^1,2 wei.yang@liu.edu, Karaesmen, Itır Z.³ ikaraes@rhsmith.umd.edu, Keskinocak, Pınar⁴ pinar@isye.gatech.edu, Tayur, Sridhar⁵ stayur@andrew.cmu.edu
Source:	Annals of Operations Research. Mar2008, Vol. 159 Issue 1, p415-431. 17p. 3 Diagrams, 4 Charts, 1 Graph.
Subjects:	Time-sharing computer systems, Multiprogramming (Electronic computers), Mathematical models, Mathematical models of consumption, Heuristic, Operations research
Abstract:	Fractional aircraft ownership programs, where individuals or corporations own a fraction of an aircraft, have revolutionized the corporate aviation industry. Fractional management companies (FMC) manage all aspects of aircraft operations enabling the owners to enjoy the benefits of private aviation without the associated responsibilities. We describe here the development of a scheduling decision support tool for a leading FMC. We present mathematical models, exact and heuristic solution methods. Our computational results using real and randomly generated data indicate that these models are quite effective in finding optimal or near-optimal solutions. The first phase of the implementation of one of these models at the FMC led to a significant improvement in effective utilization of the aircraft, reduction of costs due to reduced empty moves, and hence increased profits. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	Fractional aircraft ownership programs, where individuals or corporations own a fraction of an aircraft, have revolutionized the corporate aviation industry. Fractional management companies (FMC) manage all aspects of aircraft operations enabling the owners to enjoy the benefits of private aviation without the associated responsibilities. We describe here the development of a scheduling decision support tool for a leading FMC. We present mathematical models, exact and heuristic solution methods. Our computational results using real and randomly generated data indicate that these models are quite effective in finding optimal or near-optimal solutions. The first phase of the implementation of one of these models at the FMC led to a significant improvement in effective utilization of the aircraft, reduction of costs due to reduced empty moves, and hence increased profits. [ABSTRACT FROM AUTHOR]
ISSN:	02545330
DOI:	10.1007/s10479-007-0274-1