Optimization of urban and rural planning layout based on POI data and ACO model

Abstract To solve the problem of poor effectiveness and efficiency in traditional urban and rural planning layout optimization methods, an innovative urban and rural planning layout optimization method combining ant colony optimization algorithm with Points of Interest (POI) data is proposed. This method utilizes whale optimization algorithm to enhance the performance of ant colony optimization algorithm in dealing with complex planning problems, and processes urban and rural planning data in parallel. At the same time, the system integrates geographic and commercial information from POI data to provide multidimensional data support for planning. The experiment outcomes indicate that the improved ant colony optimization algorithm achieves an average accuracy of 97.43% in layout optimization for urban and rural planningwith root mean square error and average absolute error reaching 0.087 and 0.064, respectively. In the practical implementation analysis of the optimization model for urban and rural planning layout, the accuracy rates of optimizing the environment and road layout were 98.24% and 98.34%, respectively. In the overall evaluation of the optimization results of the model’s UR planning layout among different groups of people, the average satisfaction rate is 98.42%. The above outcomes indicate that the raised method can validly optimize urban and rural planning layout, and the optimization effect is good, improving the efficacy of urban and rural planning layout optimization and providing technical support for the field of layout optimization.