Cities are an important pillar and source of power for the development of modern society, and their development and prosperity are crucial to the stability and progress of the entire society. Therefore, the mechanism of urban growth characteristics and structure formation has long received widespread attention from researchers in various fields. As an important example of complex systems, urban systems are characterized by self-organizing phenomena. With the development and expansion of cities, most urban systems have experienced a transformation from monocentric growth to polycentric growth, and the separation of employment and residential centers has emerged. Given that urban systems are affected by multiple factors such as population, transportation, economy, and environment, their complexity brings challenges to research work. How to develop a model that can capture urban complexity while knowing which factors play a dominant role in urban evolution has become an urgent problem to be solved. In response to the above scientific issues, this research aims to construct a theoretical model consistent with realistic laws by combining spatial economics models and statistical physics related theories to explore the formation mechanism of urban polycentricity, and compare the results obtained by Monte Carlo simulation with those of real cities. The feasibility of the theoretical model proposed in this study is demonstrated by comparing the phenomena in this study, and suggestions are made for urban planning based on this.