Research on the application of improved genetic algorithm in computer mathematical modeling

Xinyuan Wu; Ruisha Tan; Lei Li; Yuyao Cao

doi:10.1117/12.2691827

23 August 2023 Research on the application of improved genetic algorithm in computer mathematical modeling

Xinyuan Wu, Ruisha Tan, Lei Li, Yuyao Cao

Proceedings Volume 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023); 1278416 (2023) https://doi.org/10.1117/12.2691827
Event: 2023 2nd International Conference on Applied Statistics, Computational Mathematics and Software Engineering (ASCMSE 2023), 2023, Kaifeng, China

Abstract

Genetic algorithm is an optimization method based on biological evolution and genetics, which has been widely used in computer mathematical modeling. This paper studies how to improve genetic algorithm to improve its application effect in computer mathematical modeling. Firstly, the basic principle and application range of genetic algorithm are introduced, then the limitations of genetic algorithm are analyzed, and the methods to improve genetic algorithm are put forward, including the improvement of selection operator, crossover operator and mutation operator. Finally, the application effect of the improved genetic algorithm in computer mathematical modeling is verified by experiments. The results show that the improved genetic algorithm has obvious improvement in optimizing the objective function and solving the optimal solution.

Citation Download Citation

Xinyuan Wu, Ruisha Tan, Lei Li, and Yuyao Cao "Research on the application of improved genetic algorithm in computer mathematical modeling", Proc. SPIE 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023), 1278416 (23 August 2023); https://doi.org/10.1117/12.2691827

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