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Application of Adaptive Genetic Algorithm in Optimal Scheduling of Aviation Materials

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  • Jinqiu Shang

Abstract

The maintenance and logistics support of aircraft are critical to the flight safety. The configuration and scheduling of air materials are the basis of maintenance and logistics. This research establishes the model of air material scheduling problem and introduces NSGA‐II genetic algorithm with adaptive design to optimize the air material scheduling arrangement. This adaptive design improves the local optimal solution problem of NSGA‐II and makes the optimal scheduling of air materials more accurate. In some cases, the improved NSGA‐II algorithm is expressed to zero deviation, which is not achieved by other traditional algorithms. The results of this research provide a solution with practical potential for aircraft material scheduling problem, which is significantly superior to traditional methods.

Suggested Citation

  • Jinqiu Shang, 2022. "Application of Adaptive Genetic Algorithm in Optimal Scheduling of Aviation Materials," Journal of Applied Mathematics, John Wiley & Sons, vol. 2022(1).
    • Handle: RePEc:wly:jnljam:v:2022:y:2022:i:1:n:1467935
    DOI: 10.1155/2022/1467935
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    References listed on IDEAS

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    1. Marina Efthymiou & Katie McCarthy & Chris Markou & John F. O’Connell, 2022. "An Exploratory Research on Blockchain in Aviation: The Case of Maintenance, Repair and Overhaul (MRO) Organizations," Sustainability, MDPI, vol. 14(5), pages 1-17, February.
    2. Sadiqi Assia & Ikram El Abbassi & Abdellah El Barkany & Moumen Darcherif & Ahmed El Biyaali, 2020. "Green Scheduling of Jobs and Flexible Periods of Maintenance in a Two-Machine Flowshop to Minimize Makespan, a Measure of Service Level and Total Energy Consumption," Advances in Operations Research, Hindawi, vol. 2020, pages 1-9, April.
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