Research on Resource Optimization Allocation Strategy of Colleges and Universities Based on Clustering Algorithm

This study aims to deeply analyze the logic of tuition pricing and resource optimization and allocation in Chinese universities, based on the latest clustering algorithm, by collecting panel data. Through extensive data analysis and effective quantitative analysis, this study seeks to continuously optimize the tuition pricing strategy and resource allocation in universities. This study collects over 20,000 panel data points, with university tuition pricing and admission rankings as core variables. By integrating university management experience, the K-means clustering algorithm is used for calculation and a visual model is created. The experiment shows that based on cluster analysis technology, the universities can tailor their tuition pricing and resource allocation strategies. By continuously combining these strategies with university resource allocation in universities, the management efficiency can be enhanced and better solutions can be found in resource utilization. In the future, to address the deficiencies of this study, more dimensions of real-time dynamic data, such as basic brand, professional ratings, economic environment, and location of universities, can be introduced to continuously improve the clustering model, providing universities with more comprehensive data and scientific methods during management.