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Aircraft and crew scheduling for fractional ownership programs.

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Title: Aircraft and crew scheduling for fractional ownership programs.
Authors: Wei Yang1,2 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]
Copyright of Annals of Operations Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="AR" term="%22Wei+Yang%22">Wei Yang</searchLink><relatesTo>1,2</relatesTo><i> wei.yang@liu.edu</i><br /><searchLink fieldCode="AR" term="%22Karaesmen%2C+Itır+Z%2E%22">Karaesmen, Itır Z.</searchLink><relatesTo>3</relatesTo><i> ikaraes@rhsmith.umd.edu</i><br /><searchLink fieldCode="AR" term="%22Keskinocak%2C+Pınar%22">Keskinocak, Pınar</searchLink><relatesTo>4</relatesTo><i> pinar@isye.gatech.edu</i><br /><searchLink fieldCode="AR" term="%22Tayur%2C+Sridhar%22">Tayur, Sridhar</searchLink><relatesTo>5</relatesTo><i> stayur@andrew.cmu.edu</i>
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  Data: <searchLink fieldCode="JN" term="%22Annals+of+Operations+Research%22">Annals of Operations Research</searchLink>. Mar2008, Vol. 159 Issue 1, p415-431. 17p. 3 Diagrams, 4 Charts, 1 Graph.
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  Data: 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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  Data: <i>Copyright of Annals of Operations Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s10479-007-0274-1
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