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Airline planning benchmark problems—Part II : passenger groups, utility and demand allocation

Akartunali, Kerem and Boland, Natashia and Evans, Ian and Wallace, Mark and Waterer, Hamish (2013) Airline planning benchmark problems—Part II : passenger groups, utility and demand allocation. Computers & Operations Research, 40 (3). pp. 793-804. ISSN 0305-0548

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    Abstract

    This paper is the second of two papers entitled “Airline Planning Benchmark Problems”, aimed at developing benchmark data that can be used to stimulate innovation in airline planning, in particular, in flight schedule design and fleet assignment. The former has, to date, been under-represented in the optimisation literature, due in part to the difficulty of obtaining data that adequately reflects passenger choice, and hence schedule revenue. Revenue models in airline planning optimisation only roughly approximate the passenger decision process. However, there is a growing body of literature giving empirical insights into airline passenger choice. Here we propose a new paradigm for passenger modelling, that enriches our representation of passenger revenue, in a form designed to be useful for optimisation. We divide the market demand into market segments, or passenger groups, according to characteristics that differentiate behaviour in terms of airline product selection. Each passenger group has an origin, destination, size (number of passengers), departure time window, and departure time utility curve, indicating willingness to pay for departure in time sub-windows. Taking as input market demand for each origin–destination pair, we describe a process by which we construct realistic passenger group data, based on the analysis of empirical airline data collected by our industry partner. We give the results of that analysis, and describe 33 benchmark instances produced.

    Item type: Article
    ID code: 39590
    Keywords: airline planning, passenger choice models, revenue models, benchmark data, Management. Industrial Management, Modelling and Simulation, Management Science and Operations Research, Computer Science(all)
    Subjects: Social Sciences > Industries. Land use. Labor > Management. Industrial Management
    Department: Strathclyde Business School > Management Science
    Related URLs:
    Depositing user: Pure Administrator
    Date Deposited: 08 May 2012 11:45
    Last modified: 27 Mar 2014 19:26
    URI: http://strathprints.strath.ac.uk/id/eprint/39590

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