<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>With the construction of China’s socialist modernization, the social demand for practical talents is increasing. In this paper, in the multi-objective optimization problem of social practice parenting in colleges and universities, each planning objective is assigned to select an adaptability function. And the individuals are sorted and stratified according to the calculated fitness values to generate sub-fitness tasks that are more suitable for promoting individuals in each layer. Finally, using college students and faculty members from five universities in province G as a research case, the entropy weight method is used to calculate the weights of secondary indicators in the multi-objective optimization model, which together form a set of particle vectors and search for the optimal solution within a limited range. The results show that the final calculation of the indicators affecting social practice in colleges and universities yields a mean value of 4.27, close to the set value of 5. It shows that the multi-objective optimization has good adaptability and the solution results are more accurate. At the same time, it is found that the empirical measurements are all in line with the actual situation of the universities, which once again shows that the model’s design is reasonable and practical.</p>
</abstract>

With the construction of China’s socialist modernization, the social demand for practical talents is increasing. In this paper, in the multi-objective optimization problem of social practice parenting in colleges and universities, each planning objective is assigned to select an adaptability function. And the individuals are sorted and stratified according to the calculated fitness values to generate sub-fitness tasks that are more suitable for promoting individuals in each layer. Finally, using college students and faculty members from five universities in province G as a research case, the entropy weight method is used to calculate the weights of secondary indicators in the multi-objective optimization model, which together form a set of particle vectors and search for the optimal solution within a limited range. The results show that the final calculation of the indicators affecting social practice in colleges and universities yields a mean value of 4.27, close to the set value of 5. It shows that the multi-objective optimization has good adaptability and the solution results are more accurate. At the same time, it is found that the empirical measurements are all in line with the actual situation of the universities, which once again shows that the model’s design is reasonable and practical.

Optimization of the realization of social practice cultivation function in colleges and universities combined with multi-objective optimization algorithm

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

With the construction of China’s socialist modernization, the social demand for practical talents is increasing. In this paper, in the multi-objective...

Optimization of the realization of social practice cultivation function in colleges and universities combined with multi-objective optimization algorithm

Publié en ligne: 26 févr. 2024

Pages: -

Reçu: 04 janv. 2024

Accepté: 12 janv. 2024

DOI: https://doi.org/10.2478/amns-2024-0386

Mots clés
Multi-objective optimization, Fitness function, Entropy weight method, Optimal solution, Social practice parenting

© 2024 Qing Zhou et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Optimization of the realization of social practice cultivation function in colleges and universities combined with multi-objective optimization algorithm

Publié en ligne: 26 févr. 2024

Pages: -

Reçu: 04 janv. 2024

Accepté: 12 janv. 2024

DOI: https://doi.org/10.2478/amns-2024-0386

Mots clésMulti-objective optimization, Fitness function, Entropy weight method, Optimal solution, Social practice parenting

© 2024 Qing Zhou et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Multi-objective optimization, Fitness function, Entropy weight method, Optimal solution, Social practice parenting