Abstract: This study is based on the sequencing adaptive genetic algorithm and conducts an in-depth discussion on optimization issues in the field of higher vocational sports training. By analyzing the shortcomings of traditional genetic algorithms in optimizing training plans, a new sequencing adaptive genetic algorithm is proposed to improve the optimization effect and adaptability of training plans. First, the optimization goals and constraints in higher vocational sports training were studied, including the diversity of training content and the rationality of training intensity. Secondly, based on the sequencing adaptive genetic algorithm, an optimization algorithm framework suitable for higher vocational sports training was designed, including key steps such as individual coding, fitness evaluation, and crossover mutation. Then, the proposed algorithm was verified and analyzed using experimental data. The results showed that the algorithm can effectively improve the optimization effect of the training plan and has strong adaptability and generalization capabilities. Finally, through comparison with traditional genetic algorithms and other optimization algorithms, the superiority and practicability of sequencing adaptive genetic algorithms in higher vocational sports training are further verified.

Quanzhong Gao, “Physical Training in Higher Vocational Colleges Based on Sequencing Adaptive Genetic Algorithm” International Journal of Advanced Computer Science and Applications(IJACSA), 15(2), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0150208

@article{Gao2024,
title = {Physical Training in Higher Vocational Colleges Based on Sequencing Adaptive Genetic Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0150208},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0150208},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {2},
author = {Quanzhong Gao}
}