IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v221y2014i1p211-23810.1007-s10479-013-1376-6.html
   My bibliography  Save this article

Heuristics for flight and maintenance planning of mission aircraft

Author

Listed:
  • George Kozanidis
  • Andreas Gavranis
  • George Liberopoulos

Abstract

Flight and Maintenance Planning (FMP) of mission aircraft addresses the question of which available aircraft to fly and for how long, and which grounded aircraft to perform maintenance operations on, in a group of aircraft that comprise a unit. The objective is to achieve maximum fleet availability of the unit over a given planning horizon, while also satisfying certain flight and maintenance requirements. The application of exact methodologies for the solution of the problem is quite limited, as a result of their excessive computational requirements. In this work, we prove several important properties of the FMP problem, and we use them to develop two heuristic procedures for solving large-scale FMP instances. The first heuristic is based on a graphical procedure which is currently used for generating flight and maintenance plans of mission aircraft by many Air Force organizations worldwide. The second heuristic is based on the idea of splitting the original problem into smaller sub-problems and solving each sub-problem separately. Both heuristics have been roughly sketched in earlier works that have appeared in the related literature. The present paper develops the theoretical background on which these heuristics are based, provides in detail the algorithmic steps required for their implementation, analyzes their worst-case computational complexity, presents computational results illustrating their computational performance on random problem instances, and evaluates the quality of the solutions that they produce. The size and parameter values of some of the randomly tested problem instances are quite realistic, making it possible to infer the performance of the heuristics on real world problem instances. Our computational results demonstrate that, under careful consideration, even large FMP instances can be handled quite effectively. The theoretical results and insights that we develop establish a fundamental background that can be very useful for future theoretical and practical developments related to the FMP problem. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • George Kozanidis & Andreas Gavranis & George Liberopoulos, 2014. "Heuristics for flight and maintenance planning of mission aircraft," Annals of Operations Research, Springer, vol. 221(1), pages 211-238, October.
    • Handle: RePEc:spr:annopr:v:221:y:2014:i:1:p:211-238:10.1007/s10479-013-1376-6
    DOI: 10.1007/s10479-013-1376-6
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-013-1376-6
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-013-1376-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. George Kozanidis & Andreas Gavranis & Eftychia Kostarelou, 2012. "Mixed integer least squares optimization for flight and maintenance planning of mission aircraft," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(3‐4), pages 212-229, April.
    2. Ville Mattila & Kai Virtanen & Tuomas Raivio, 2008. "Improving Maintenance Decision Making in the Finnish Air Force Through Simulation," Interfaces, INFORMS, vol. 38(3), pages 187-201, June.
    3. Ram Gopalan & Kalyan Talluri, 1998. "Mathematical models in airline schedule planning: A survey," Annals of Operations Research, Springer, vol. 76(0), pages 155-185, January.
    4. Nima Safaei & Dragan Banjevic & Andrew Jardine, 2011. "Workforce-constrained maintenance scheduling for military aircraft fleet: a case study," Annals of Operations Research, Springer, vol. 186(1), pages 295-316, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marvin L. King & David R. Galbreath & Alexandra M. Newman & Amanda S. Hering, 2020. "Combining regression and mixed-integer programming to model counterinsurgency," Annals of Operations Research, Springer, vol. 292(1), pages 287-320, September.
    2. Feng, Qiang & Bi, Xiong & Zhao, Xiujie & Chen, Yiran & Sun, Bo, 2017. "Heuristic hybrid game approach for fleet condition-based maintenance planning," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 166-176.
    3. Cha, Guesik & Park, Junseok & Moon, Ilkyeong, 2023. "Military aircraft flight and maintenance planning model considering heterogeneous maintenance tasks," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    4. Gavranis, Andreas & Kozanidis, George, 2015. "An exact solution algorithm for maximizing the fleet availability of a unit of aircraft subject to flight and maintenance requirements," European Journal of Operational Research, Elsevier, vol. 242(2), pages 631-643.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. George Kozanidis & Andreas Gavranis & Eftychia Kostarelou, 2012. "Mixed integer least squares optimization for flight and maintenance planning of mission aircraft," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(3‐4), pages 212-229, April.
    2. Gavranis, Andreas & Kozanidis, George, 2015. "An exact solution algorithm for maximizing the fleet availability of a unit of aircraft subject to flight and maintenance requirements," European Journal of Operational Research, Elsevier, vol. 242(2), pages 631-643.
    3. De Bruecker, Philippe & Van den Bergh, Jorne & Beliën, Jeroen & Demeulemeester, Erik, 2015. "A model enhancement heuristic for building robust aircraft maintenance personnel rosters with stochastic constraints," European Journal of Operational Research, Elsevier, vol. 246(2), pages 661-673.
    4. Dilaver, Halit Metehan & Akçay, Alp & van Houtum, Geert-Jan, 2023. "Integrated planning of asset-use and dry-docking for a fleet of maritime assets," International Journal of Production Economics, Elsevier, vol. 256(C).
    5. Yonit Barron, 2018. "Group maintenance policies for an R-out-of-N system with phase-type distribution," Annals of Operations Research, Springer, vol. 261(1), pages 79-105, February.
    6. Marvin L. King & David R. Galbreath & Alexandra M. Newman & Amanda S. Hering, 2020. "Combining regression and mixed-integer programming to model counterinsurgency," Annals of Operations Research, Springer, vol. 292(1), pages 287-320, September.
    7. Carlos Lagos & Felipe Delgado & Mathias A. Klapp, 2020. "Dynamic Optimization for Airline Maintenance Operations," Transportation Science, INFORMS, vol. 54(4), pages 998-1015, July.
    8. Saravanan Venkatachalam & Suresh Acharya & Kenji Oba & Yoshinari Nakayama, 2020. "Prescriptive Analytics for Swapping Aircraft Assignments at All Nippon Airways," Interfaces, INFORMS, vol. 50(2), pages 99-111, March.
    9. Turan, Hasan Hüseyin & Jalalvand, Fatemeh & Elsawah, Sondoss & Ryan, Michael J., 2022. "A joint problem of strategic workforce planning and fleet renewal: With an application in defense," European Journal of Operational Research, Elsevier, vol. 296(2), pages 615-634.
    10. Feng, Qiang & Bi, Xiong & Zhao, Xiujie & Chen, Yiran & Sun, Bo, 2017. "Heuristic hybrid game approach for fleet condition-based maintenance planning," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 166-176.
    11. Nima Safaei & Dragan Banjevic & Andrew Jardine, 2011. "Workforce-constrained maintenance scheduling for military aircraft fleet: a case study," Annals of Operations Research, Springer, vol. 186(1), pages 295-316, June.
    12. Uğur Arıkan & Sinan Gürel & M. Aktürk, 2016. "Integrated aircraft and passenger recovery with cruise time controllability," Annals of Operations Research, Springer, vol. 236(2), pages 295-317, January.
    13. Budai-Balke, G. & Dekker, R. & Nicolai, R.P., 2006. "A review of planning models for maintenance and production," Econometric Institute Research Papers EI 2006-44, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    14. Zhang, Qin & Liu, Yu & Xiahou, Tangfan & Huang, Hong-Zhong, 2023. "A heuristic maintenance scheduling framework for a military aircraft fleet under limited maintenance capacities," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    15. De Bruecker, Philippe & Van den Bergh, Jorne & Beliën, Jeroen & Demeulemeester, Erik, 2015. "Workforce planning incorporating skills: State of the art," European Journal of Operational Research, Elsevier, vol. 243(1), pages 1-16.
    16. A T Ernst & M Horn & P Kilby & M Krishnamoorthy, 2010. "Dynamic scheduling of recreational rental vehicles with revenue management extensions," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(7), pages 1133-1143, July.
    17. Joachim Arts & Simme Flapper, 2015. "Aggregate overhaul and supply chain planning for rotables," Annals of Operations Research, Springer, vol. 224(1), pages 77-100, January.
    18. Van den Bergh, Jorne & Beliën, Jeroen & De Bruecker, Philippe & Demeulemeester, Erik & De Boeck, Liesje, 2013. "Personnel scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 226(3), pages 367-385.
    19. Pritibhushan Sinha, 2012. "A random maintenance scheduling model to reduce fault diagnosis time," Annals of Operations Research, Springer, vol. 201(1), pages 441-447, December.
    20. Jamili, Amin, 2017. "A robust mathematical model and heuristic algorithms for integrated aircraft routing and scheduling, with consideration of fleet assignment problem," Journal of Air Transport Management, Elsevier, vol. 58(C), pages 21-30.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:221:y:2014:i:1:p:211-238:10.1007/s10479-013-1376-6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.