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Assessment of aircraft logistics planning models

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  • Geisler, Murray A
  • Murrie, Bruce L

Abstract

An assessment of military logistics planning models offers a great deal of information about the modelling state of art. Such tools include both analytic and simulation model types. They can deal with both static and dynamic characteristics of the environment. They require highly detailed data for their operation and can compute over a large number of interacting variables. Unfortunately, these models do not satisfy adequately the requirements of the particular logistics issue for which they were assessed, which is whether such models can be used in early logistics planning for new weapon systems. One difficulty is that such planning must make extensive use of tradeoffs and sensitivity analysis to take account of the flexibility and uncertainties existing at the early stages. Another is that the existent models call for detailed data which is usually not available at that time. Therefore, although the models do fulfill a particular useful planning function, they must be replaced or augmented by a new class of models that will much more closely satisfy the planning need. This new capability requires a serious research effort that will benefit not only the military logistics planners, but also other planners dealing with large capital development programs.

Suggested Citation

  • Geisler, Murray A & Murrie, Bruce L, 1981. "Assessment of aircraft logistics planning models," Omega, Elsevier, vol. 9(1), pages 59-69.
  • Handle: RePEc:eee:jomega:v:9:y:1981:i:1:p:59-69
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    Cited by:

    1. Hatch, Melanie L. & Badinelli, Ralph D., 1999. "Concurrent optimization in designing for logistics support," European Journal of Operational Research, Elsevier, vol. 115(1), pages 77-97, May.
    2. Sohn, So Young & Han, Hong Kyu & Jeon, Hye Jin, 2007. "Development of an Air Force Warehouse Logistics Index to continuously improve logistics capabilities," European Journal of Operational Research, Elsevier, vol. 183(1), pages 148-161, November.

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