Engineering project management technology based on visual simulation module and particle swarm optimization

Abstract

In recent years, China’s construction industry has developed rapidly, but it still faces problems such as complex processes, long cycles, and unpredictable environments in engineering projects. To address these issues, a building information modeling development and design based on visual management was proposed to improve the efficiency of collecting and analyzing engineering data and information. At the same time, the particle swarm multi-objective optimization algorithm was adopted to comprehensively analyze the influencing factors during the operation of the module. The results indicated that the response time of the building information model in information processing did not exceed 20% of the total time. By using this method, the project cost prediction error reduced to 30–80 yuan, which demonstrated the accuracy of building information modeling technology. Compared with the efficiency value of the algorithm in the first 10s, the traditional single objective optimization algorithm was 0.28, while the proposed algorithm was 0.40. This significant improvement indicated that the development of building information models could effectively improve the efficiency of information flow. The particle swarm multi-objective optimization algorithm performed well in reducing project cost prediction errors. The results of this study have promoted the information process of the construction industry and provided strong support for achieving efficient and accurate engineering management.