Community Sports Facility Ant Colony Algorithm Collocation under the Environment of National Fitness

Abstract

The construction of sports facilities is gradually gaining public attention in the national fitness environment. Community sports facilities make a great contribution in making up for the shortage of urban gymnasiums, but there are many similarities in the existing community sports facilities, and the collocation is only to meet the basic needs. Based on this, this paper investigates the study of an ant colony algorithm for the collocation of community sports facilities in a national fitness environment. Based on a brief analysis of the construction of community sports facilities and the study of ant colony algorithms, a model of community sports facility matching is constructed and an ant colony algorithm is introduced to optimize the design of the scheme. The multiobjective function model is combined with the demand for community sports settings collocation, and the optimal solution set for different planning objectives is proposed in the optimal design of sports facility collocation. The objective function is combined with the ant colony algorithm to continuously update the objective function value and obtain the optimal solution after stabilization, providing a more excellent configuration for sports facility collocation. The simulation results show that the performance of this algorithm is more stable than that of traditional algorithms, and it can provide more diverse solutions for sports facility matching with greater stability.