Optimization of Construction Resources for Prefabricated Buildings Based on an Improved PSO Algorithm Driven by BIM

With the deep application of technologies such as artificial intelligence in the field of construction project management, improving the optimization of construction resources for prefabricated buildings using intelligent technologies has become an urgent issue to be addressed. Based on this, the study proposes a resource optimization scheme that integrates building information modeling (BIM) technology and particle swarm optimization (PSO) algorithms. BIM technology is used to construct a three-dimensional building model that contains geometric information and parameter attributes, enabling the accurate extraction of multidimensional resource demand data during the construction process and providing an accurate data foundation for the optimization algorithm. At the same time, a multi-vector optimization strategy is introduced to expand the search dimensions of the particle swarm algorithm, enhance its global search capabilities, and effectively avoid premature convergence issues. Experimental results demonstrate that the improved resource optimization method exhibits superior global search capabilities, reducing the daily peak demand for Resource A and Resource B to 6 and 4, respectively, with the maximum daily human resource demand decreasing by 24%. Resource utilization rates have been effectively improved. Empirical data indicate that the proposed method can provide reliable and effective resource optimization solutions for prefabricated building projects, thereby offering technical support for the intelligent transformation of the construction industry.