IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v62y2011i2d10.1057_jors.2010.119.html
   My bibliography  Save this article

An advanced tabu search for solving the mixed payload airlift loading problem

Author

Listed:
  • R L Nance

    (Air Force Institute of Technology, Wright Patterson AFB)

  • A G Roesener

    (Air Force Institute of Technology, Wright Patterson AFB)

  • J T Moore

    (Air Force Institute of Technology, Wright Patterson AFB)

Abstract

This article describes a new, two-dimensional bin packing algorithm that feasibly loads a set of cargo items on a minimal set of airlift aircraft. The problem under consideration is called the Mixed Payload Airlift Loading Problem (MPALP). The heuristic algorithm, called the Mixed Payload Airlift Loading Problem Tabu Search (MPALPTS), surpasses previous research conducted in this area because, in addition to pure pallet cargo loads, MPALPTS can accommodate rolling stock cargo (ie tanks, trucks, HMMMVs, etc) while still maintaining feasibility. To demonstrate its effectiveness, the load plans generated by MPALPTS are directly compared to those generated by the Automated Air Load Planning Software (AALPS) for a given cargo set; AALPS is the load planning software currently mandated for use in all Department of Defense load planning. While more time consuming than AALPS, MPALPTS required the same or fewer aircraft than AALPS in all test scenarios.

Suggested Citation

  • R L Nance & A G Roesener & J T Moore, 2011. "An advanced tabu search for solving the mixed payload airlift loading problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(2), pages 337-347, February.
    • Handle: RePEc:pal:jorsoc:v:62:y:2011:i:2:d:10.1057_jors.2010.119
    DOI: 10.1057/jors.2010.119
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/jors.2010.119
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/jors.2010.119?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. Chaitr S. Hiremath & Raymond R. Hill, 2007. "New greedy heuristics for the Multiple-choice Multi-dimensional Knapsack Problem," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 2(4), pages 495-512.
    2. Fred Glover, 1989. "Tabu Search---Part I," INFORMS Journal on Computing, INFORMS, vol. 1(3), pages 190-206, August.
    3. Kurt R. Heidelberg & Gregory S. Parnell & James E. Ames, 1998. "Automated air load planning," Naval Research Logistics (NRL), John Wiley & Sons, vol. 45(8), pages 751-768, December.
    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. Brandt, Felix & Nickel, Stefan, 2019. "The air cargo load planning problem - a consolidated problem definition and literature review on related problems," European Journal of Operational Research, Elsevier, vol. 275(2), pages 399-410.
    2. Lurkin, Virginie & Schyns, Michaël, 2015. "The Airline Container Loading Problem with pickup and delivery," European Journal of Operational Research, Elsevier, vol. 244(3), pages 955-965.

    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. Chiara Gruden & Irena Ištoka Otković & Matjaž Šraml, 2020. "Neural Networks Applied to Microsimulation: A Prediction Model for Pedestrian Crossing Time," Sustainability, MDPI, vol. 12(13), pages 1-22, July.
    2. Сластников С.А., 2014. "Применение Метаэвристических Алгоритмов Для Задачи Маршрутизации Транспорта," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 50(1), pages 117-126, январь.
    3. Nair, D.J. & Grzybowska, H. & Fu, Y. & Dixit, V.V., 2018. "Scheduling and routing models for food rescue and delivery operations," Socio-Economic Planning Sciences, Elsevier, vol. 63(C), pages 18-32.
    4. Cazzaro, Davide & Fischetti, Martina & Fischetti, Matteo, 2020. "Heuristic algorithms for the Wind Farm Cable Routing problem," Applied Energy, Elsevier, vol. 278(C).
    5. Kadri Sylejmani & Jürgen Dorn & Nysret Musliu, 2017. "Planning the trip itinerary for tourist groups," Information Technology & Tourism, Springer, vol. 17(3), pages 275-314, September.
    6. Huang, Yeran & Yang, Lixing & Tang, Tao & Gao, Ziyou & Cao, Fang, 2017. "Joint train scheduling optimization with service quality and energy efficiency in urban rail transit networks," Energy, Elsevier, vol. 138(C), pages 1124-1147.
    7. B Dengiz & C Alabas-Uslu & O Dengiz, 2009. "Optimization of manufacturing systems using a neural network metamodel with a new training approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(9), pages 1191-1197, September.
    8. S-W Lin & K-C Ying, 2008. "A hybrid approach for single-machine tardiness problems with sequence-dependent setup times," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(8), pages 1109-1119, August.
    9. Joseph B. Mazzola & Robert H. Schantz, 1997. "Multiple‐facility loading under capacity‐based economies of scope," Naval Research Logistics (NRL), John Wiley & Sons, vol. 44(3), pages 229-256, April.
    10. Kadri Sylejmani & Jürgen Dorn & Nysret Musliu, 0. "Planning the trip itinerary for tourist groups," Information Technology & Tourism, Springer, vol. 0, pages 1-40.
    11. Abdmouleh, Zeineb & Gastli, Adel & Ben-Brahim, Lazhar & Haouari, Mohamed & Al-Emadi, Nasser Ahmed, 2017. "Review of optimization techniques applied for the integration of distributed generation from renewable energy sources," Renewable Energy, Elsevier, vol. 113(C), pages 266-280.
    12. Masoud Yaghini & Mohammad Karimi & Mohadeseh Rahbar, 2015. "A set covering approach for multi-depot train driver scheduling," Journal of Combinatorial Optimization, Springer, vol. 29(3), pages 636-654, April.
    13. Chris S. K. Leung & Henry Y. K. Lau, 2018. "Multiobjective Simulation-Based Optimization Based on Artificial Immune Systems for a Distribution Center," Journal of Optimization, Hindawi, vol. 2018, pages 1-15, May.
    14. Ilfat Ghamlouche & Teodor Gabriel Crainic & Michel Gendreau, 2003. "Cycle-Based Neighbourhoods for Fixed-Charge Capacitated Multicommodity Network Design," Operations Research, INFORMS, vol. 51(4), pages 655-667, August.
    15. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part II: Metaheuristics," Transportation Science, INFORMS, vol. 39(1), pages 119-139, February.
    16. Andaryan, Abdullah Zareh & Mousighichi, Kasra & Ghaffarinasab, Nader, 2024. "A heuristic approach to the stochastic capacitated single allocation hub location problem with Bernoulli demands," European Journal of Operational Research, Elsevier, vol. 312(3), pages 954-968.
    17. L Tang & X Wang, 2008. "An iterated local search heuristic for the capacitated prize-collecting travelling salesman problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(5), pages 590-599, May.
    18. Gintaras Palubeckis & Dalius Rubliauskas, 2012. "A branch-and-bound algorithm for the minimum cut linear arrangement problem," Journal of Combinatorial Optimization, Springer, vol. 24(4), pages 540-563, November.
    19. Panta Lučić & Dušan Teodorović, 2007. "Metaheuristics approach to the aircrew rostering problem," Annals of Operations Research, Springer, vol. 155(1), pages 311-338, November.
    20. Smutnicki, Czeslaw & Pempera, Jaroslaw & Bocewicz, Grzegorz & Banaszak, Zbigniew, 2022. "Cyclic flow-shop scheduling with no-wait constraints and missing operations," European Journal of Operational Research, Elsevier, vol. 302(1), pages 39-49.

    More about this item

    Keywords

    military; heuristic; logistics;
    All these keywords.

    Statistics

    Access and download statistics

    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:pal:jorsoc:v:62:y:2011:i:2:d:10.1057_jors.2010.119. 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.palgrave-journals.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.