JOURNAL ARTICLE
Optimal Flight and Maintenance Planning of a Military Aircraft Fleet through to Life-of-Type.
Published In: Military Operations Research, 2025, v. 30, n. 1. P. 5 1 of 3
Database: Military & Government Collection 2 of 3
Authored By: Marlow, David O.; Dell, Robert F. 3 of 3
Abstract
Fleet planners of military aircraft have many competing priorities. This results in a difficult balancing act between meeting short-term immediate tasking needs and long-term management. If short-term needs always take precedence, it is likely that the fleet will be unable to meet those same needs in the future. This is particularly important in appropriately managing a fleet to retirement, such that aircraft are neither over-utilized (forcing them to retire before the rest of the fleet) or under-utilized (retiring them with unused flying hours). In this article, we present a mixed integer linear program (MIP) for optimal aircraft fleet management over a multiple-year time horizon, up to life-of-type. The MIP is run at various timescales and time steps. It solves with multiple weighted objectives, or iteratively in descending order of lexicographic priority. It prescribes decisions to include when to deploy each aircraft, when to induct aircraft into depot maintenance within an induction window, when to induct aircraft into modification programs (on a dedicated line or as part of depot maintenance), and how to fly aircraft in order to both meet ongoing fleet and squadron requirements, and reach retirement targets. We demonstrate the MIP's capability with several examples based on real-world experience. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Military Operations Research. 2025/01, Vol. 30, Issue 1, p5
- Document Type:Article
- Subject Area:Military History and Science
- Publication Date:2025
- ISSN:1082-5983
- DOI:10.5711/1082598330105
- Accession Number:184606413
- Copyright Statement:Copyright of Military Operations Research is the property of Military Operations Research Society 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.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.