Against the background of accelerated urbanization and increasing health consciousness of residents, the rational allocation of sports facilities in residential communities has become an important factor affecting the quality of life of residents. The concept of health-oriented community construction incorporating the elements of Civics and Politics provides new ideas for the optimization of sports facilities. This paper proposes a health-oriented residential design sports facilities site selection optimization model based on improved ant colony algorithm. The study proposes an improved ant colony algorithm for the shortcomings of the traditional ant colony algorithm in sports facility siting, which has slow convergence speed and is easy to fall into the local optimum. The algorithm is optimized by resetting the initial pheromone distribution, improving the pheromone volatility factor and combining the local search strategy. The site selection objective function is constructed based on the ArcGIS raster data model, and factors such as population density, distance cost and facility attractiveness are considered comprehensively. The experimental results show that the average value of system elapsed time of the improved algorithm is 247.11s, which improves the efficiency by 12.57% compared with the traditional ant colony algorithm. In the application of sports facility siting, the average siting time of the algorithm is 3.60s, and the facility coverage rate reaches 93.12%, which significantly improves the siting efficiency and service quality. The study verifies the effectiveness of the improved ant colony algorithm in the optimization of sports facilities in housing design, provides a scientific decision support tool for the construction of health-oriented community based on the elements of Civics, and is of practical value for improving the level of sports facilities allocation in residential areas.
