A network Airline Revenue Management Framework Based on Deccomposition by Origins ans Destinations

S.I. Birbil, J.B.G. Frenk, J.A. Gromicho Dos Santos, Shuzhong Zhang

Abstract

We propose a framework for solving airline revenue management problems on large networks, where the main concern is to allocate the flight leg capacities to customer requests under fixed class fares. This framework is based on a mathematical programming model that decomposes the network into origin-destination pairs so that each pair can be treated as a single flight-leg problem. We first discuss that the proposed framework is quite generic in the sense that not only several well-known models from the literature fit into this framework, but also many single flight-leg models can be easily extended to a network setting through the prescribed construction. Then, we analyze the structure of the overall mathematical programming model and establish its relationship with other models frequently used in practice. The application of the proposed framework is illustrated through two examples based on static and dynamic single-leg models, respectively. These illustrative examples are then benchmarked against several existing methods on a set of real-life network problems.
Original languageEnglish
Pages (from-to)313-333
JournalTransportation Science
Volume48
Issue number3
DOIs
StatePublished - 2014

Cite this

Birbil, S.I.; Frenk, J.B.G.; Gromicho Dos Santos, J.A.; Zhang, Shuzhong / A network Airline Revenue Management Framework Based on Deccomposition by Origins ans Destinations.

In: Transportation Science, Vol. 48, No. 3, 2014, p. 313-333.

Research output: Scientific - peer-reviewArticle

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abstract = "We propose a framework for solving airline revenue management problems on large networks, where the main concern is to allocate the flight leg capacities to customer requests under fixed class fares. This framework is based on a mathematical programming model that decomposes the network into origin-destination pairs so that each pair can be treated as a single flight-leg problem. We first discuss that the proposed framework is quite generic in the sense that not only several well-known models from the literature fit into this framework, but also many single flight-leg models can be easily extended to a network setting through the prescribed construction. Then, we analyze the structure of the overall mathematical programming model and establish its relationship with other models frequently used in practice. The application of the proposed framework is illustrated through two examples based on static and dynamic single-leg models, respectively. These illustrative examples are then benchmarked against several existing methods on a set of real-life network problems.",
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A network Airline Revenue Management Framework Based on Deccomposition by Origins ans Destinations. / Birbil, S.I.; Frenk, J.B.G.; Gromicho Dos Santos, J.A.; Zhang, Shuzhong.

In: Transportation Science, Vol. 48, No. 3, 2014, p. 313-333.

Research output: Scientific - peer-reviewArticle

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AB - We propose a framework for solving airline revenue management problems on large networks, where the main concern is to allocate the flight leg capacities to customer requests under fixed class fares. This framework is based on a mathematical programming model that decomposes the network into origin-destination pairs so that each pair can be treated as a single flight-leg problem. We first discuss that the proposed framework is quite generic in the sense that not only several well-known models from the literature fit into this framework, but also many single flight-leg models can be easily extended to a network setting through the prescribed construction. Then, we analyze the structure of the overall mathematical programming model and establish its relationship with other models frequently used in practice. The application of the proposed framework is illustrated through two examples based on static and dynamic single-leg models, respectively. These illustrative examples are then benchmarked against several existing methods on a set of real-life network problems.

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