Multi-objective optimization regulation method and intelligent path planning of ideological and political education elements in physical education teaching

Curriculum Civics reform in physical education should keep pace with the times and actively explore modern technical means.This study addresses the problem of regulating the elements of Civic and political education in physical education, and establishes a mathematical model of multi-objective optimization and regulation by comprehensively considering the various factors and constraints involved in the problem.In order to further optimize the regulation results, an improved two-population genetic algorithm is used to solve the model.Taking the physical education course of a university as an example to analyze, the design algorithm of this paper is compared with the experiments, and the improved two-population genetic algorithm completes the convergence in 300 iterations, and the degree of adaptability is improved by 2.04%, which has the characteristics of strong global search ability and fast convergence speed, which proves that the improved two-population genetic algorithm has a certain degree of superiority and validity.The utilization rate of the elements of ideology and politics education in the experimental solution results reaches 0.87, and other factors meet the actual needs of sports teaching, and the method of this paper can realize the intelligent regulation of the elements of ideology and politics education in sports teaching.