Development and visualization of the computer loadıng plannıng model for the cargo aırcraft

Authors

DOI:

https://doi.org/10.15587/1729-4061.2021.235629

Keywords:

freight container (ULD), optimal load, load planning algorithm, computer model, expert system

Abstract

Loading an aircraft is an extremely complex process with many variable aspects that determine the planning of each flight separately. The article is devoted to the development of an algorithm and a computer model for planning the loading of a cargo ramp aircraft in a multi-lag route. The essence of the algorithm consists in a predetermined arrangement of cargo containers relative to the cargo compartment, taking into account the general limitations of the aircraft and the priority of the cargo, which directly affects the planning of loading in a multi-lag route. The use of a visualized computer model created on the basis of the algorithm can reduce the average time of loading operations for a number of direct flights by almost 7 %, and on multi-lag flights by 12 %.

Implementation of the model in the activities of an air carrier avoids a situation where certain criteria and restrictions entail sorting «manually» by all indicators, which is very time-consuming in the context of the urgency of servicing the aircraft at the airport.

The visualized load planning computer model enables flight planning personnel to make faster decisions and predict additional load on other sections of the route.

The successful application of the model to the airline’s operations contributes to the efficiency and safety of ground handling services. This contributes to the intensification of the use of the aircraft fleet by increasing the speed of commercial cargo handling.

In the future, the computer model can serve as the basis for a rule-based expert system in order to prevent containers from being overloaded at intermediate sections of the route

Author Biographies

Yelyzaveta Sahun, Flight Academy of National Aviation University

Postgraduate Student

Department of Flight Exploitation, Aerodynamics and Flight Dynamics

Anatoliy Zalevskii, Flight Academy of National Aviation University

PhD, Associate Professor

Department of Tourism and Air Transportations

Natalya Chornohor, National Aviation University

PhD, Senior Lecturer

Department of Tourism and Air Transportations

Yuliya Sikirda, Flight Academy of National Aviation University

PhD, Associate Professor

Department of Tourism and Air Transportations

References

  1. Sahun, A., Sahun, Y. (2019). Technological peculiarities of aircraft loading process. Scientific Bulletin of Flight Academy. Section: Economics, Management and Law, 1, 84–90. doi: https://doi.org/10.33251/2707-8620-2019-1-84-90
  2. Sahun, Y. S. (2020). Perspective Directions of Artificial Intelligence Systems in Aircraft Load Optimization Process. Advances in Mechatronics and Mechanical Engineering, 419–437. doi: https://doi.org/10.4018/978-1-7998-1415-3.ch018
  3. Air-Freight Forwarders Move Forward into a Digital Future. McKinsey & Company Travel. Available at: https://www.mckinsey.com/industries/travel-logistics-and-transport-infrastructure/our-insights/air-freight-forwarders-move-forward-into-a-digital-future
  4. Guéret, C., Jussien, N., Lhomme, O., Pavageau, C., Prins, C. (2003). Loading aircraft for military operations. Journal of the Operational Research Society, 54 (5), 458–465. doi: https://doi.org/10.1057/palgrave.jors.2601551
  5. Souffriau, W., Demeester, P., Vanden Berghe, G., De Causmaecker, P. (2008). The Aircraft Weight and Balance Problem. 22nd national conference of the Belgian Operations Research Society, 44–45.
  6. Hussein, M. I. (2012). Container Handling Algorithms and Outbound Heavy Truck Movement Modeling for Seaport Container Transshipment Terminals. University of Wisconsin Milwaukee.
  7. Kaluzny, B., Shaw, D. (2008). Optimal aircraft load balancing. Mathematical formulation. CORA Technical Report. National Defence R&D, 15–21.
  8. Thomas, C., Campbell, K., Hines, G., Racer, M. (1998). Airbus Packing at Federal Express. Interfaces, 28 (4), 21–30. doi: https://doi.org/10.1287/inte.28.4.21
  9. Wilson, I. D., Roach, P. A., Ware, J. A. (2001). Container stowage pre-planning: using search to generate solutions, a case study. Knowledge-Based Systems, 14 (3-4), 137–145. doi: https://doi.org/10.1016/s0950-7051(01)00090-9
  10. Bortfeldt, A., Gehring, H. (2001). A hybrid genetic algorithm for the container loading problem. European Journal of Operational Research, 131 (1), 143–161. doi: https://doi.org/10.1016/s0377-2217(00)00055-2
  11. Nance, R. L., Roesener, A. G., Moore, J. T. (2011). An advanced tabu search for solving the mixed payload airlift loading problem. Journal of the Operational Research Society, 62 (2), 337–347. doi: https://doi.org/10.1057/jors.2010.119
  12. Li, F., Tian, C., Zhang, H., Kelley, W. (2010). Rule-based optimization approach for airline load planning system. Procedia Computer Science, 1 (1), 1455–1463. doi: https://doi.org/10.1016/j.procs.2010.04.161
  13. Limbourg, S., Schyns, M., Laporte, G. (2012). Automatic aircraft cargo load planning. Journal of the Operational Research Society, 63 (9), 1271–1283. doi: https://doi.org/10.1057/jors.2011.134
  14. Rukovodstvo letnoy ekspluatatsii IL-76 (1984). Izdanie 2, Prilozhenie 3: Instruktsiya po tsentrovke i zagruzke, 2–12.
  15. Sahun, Y. (2020). Priority loading algorithm as the part of aircraft load optimization model. Proceedings of the National Aviation University, 84 (3), 44–49. doi: https://doi.org/10.18372/2306-1472.84.14952

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Published

2021-06-30

How to Cite

Sahun, Y., Zalevskii, A., Chornohor, N., & Sikirda, Y. (2021). Development and visualization of the computer loadıng plannıng model for the cargo aırcraft . Eastern-European Journal of Enterprise Technologies, 3(3 (111), 24–31. https://doi.org/10.15587/1729-4061.2021.235629

Issue

Section

Control processes