Abstract: The genetic algorithm (GA), characterized by parallelism and global optimization capabilities, is well-suited for solving optimization problems related to expressway maintenance schemes. In this study, we improved GA operators and algorithm parameters within the existing maintenance scheme optimization model, thereby enhancing the operational efficiency of the GA. Building on this foundation, an optimization algorithm for expressway maintenance schemes was developed. Subsequently, MATLAB was employed to program the algorithm and solve the expressway maintenance scheme problem. When compared with the solution results in the reference, the proposed approach achieved a reduction of approximately 3.6% in maintenance costs and an improvement of about 47% in operation speed, verifying the algorithm's reliability and effectiveness. Finally, visualization of the algorithm program was enabled using MATLAB App Designer and MATLAB Compiler. This method can be popularized and applied in aspects such as expressway maintenance decision-making and optimization of building maintenance schemes.

Yushu Zhu, Xingwang Liu, Fengshuang Zhang, Kashan Khan, Yang Chen, Runqi Liu and Qiang He. “Optimal Algorithm of Expressway Maintenance Scheme Based on Genetic Algorithm”. International Journal of Advanced Computer Science and Applications (IJACSA) 16.5 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0160515

@article{Zhu2025,
title = {Optimal Algorithm of Expressway Maintenance Scheme Based on Genetic Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160515},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160515},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {5},
author = {Yushu Zhu and Xingwang Liu and Fengshuang Zhang and Kashan Khan and Yang Chen and Runqi Liu and Qiang He}
}