• DocumentCode
    48894
  • Title

    Air Cargo Demand Modeling and Prediction

  • Author

    Totamane, Raghavendra ; Dasgupta, Avirup ; Rao, Smitha

  • Volume
    8
  • Issue
    1
  • fYear
    2014
  • fDate
    Mar-14
  • Firstpage
    52
  • Lastpage
    62
  • Abstract
    The air cargo transportation system is a large and complex service system, in which demand forecasting is a key element in the master planning process. Demand forecasting is essential for analyzing existing cargo flight schedules and identifying future facility requirements of air cargo companies. We use the Potluck Problem approach to propose a multiproducer/multiconsumer solution for predicting the cargo demand of a specific airline in a given route, and the cargo load factor for a given flight schedule on that route. This solution considers each airline as a producer and the users of air cargo services as consumers, with a producer having no explicit communication with other producers/airlines. The model analyzes the existing cargo capacity plan, highlights drawbacks, and proposes a new capacity plan to demonstrate the effectiveness of using the solution. Examples are provided to illustrate the efficacy of the approach.
  • Keywords
    aircraft; demand forecasting; goods distribution; scheduling; transportation; travel industry; air cargo companies; air cargo demand modeling; air cargo demand prediction; air cargo services; air cargo transportation system; cargo capacity plan; cargo flight schedule analysis; cargo load factor; complex service system; demand forecasting; future facility requirement identification; master planning process; multiconsumer solution; multiproducer solution; potluck problem; Aircraft; Atmospheric modeling; Capacity planning; Economics; Prediction algorithms; Predictive models; Schedules; Air cargo; Potluck Problem; cargo capacity; cargo load factor; demand prediction; multiagent system; weighted majority algorithm;
  • fLanguage
    English
  • Journal_Title
    Systems Journal, IEEE
  • Publisher
    ieee
  • ISSN
    1932-8184
  • Type

    jour

  • DOI
    10.1109/JSYST.2012.2218511
  • Filename
    6317129