Abstract: The Chinese aviation transportation industry is constantly developing towards multiple objectives and constraints. The conventional optimization method for stand assignment of civil aviation aircraft has low efficiency and can no longer meet practical needs. Based on this, the paper firstly focuses on the problem of convergence and uniformity in multi-objective optimization, and uses the multi-strategy algorithm to optimize the multi-strategy algorithm of Multi-strategy competitive-cooperative co-evolutionary algorithm (MSCOEA). Then, for the problem of high time complexity in the traditional chromosome coding mode, the characteristics of quantum evolution algorithm can be reduced by MSCOEA algorithm. Front the results, the prediction accuracy of the research method was above 90% on both the training and validation sets. With the increase of iterations, the final accuracy was 96.8% and 97.53%, respectively. This algorithm achieved the same performance as some other comparative algorithms in most of the objectives. The optimal flight allocation rate reached 98.4%. The mean, optimal value, and variance of the number of flights allocated to remote stands were 5.75E+00, 4.00E+00, and 1.04E+00, respectively, which were superior to other comparative algorithms. The deigned stand assignment optimization method achieves efficient stand assignment, and improves the allocation efficiency of large and multi-objective stands.

Qiao Xue, Yaqiong Wang and Hui Hui, “Optimization Technology of Civil Aircraft Stand Assignment Based on MSCOEA Model” International Journal of Advanced Computer Science and Applications(IJACSA), 16(2), 2025. http://dx.doi.org/10.14569/IJACSA.2025.0160260

@article{Xue2025,
title = {Optimization Technology of Civil Aircraft Stand Assignment Based on MSCOEA Model},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160260},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160260},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {2},
author = {Qiao Xue and Yaqiong Wang and Hui Hui}
}