In building engineering project management, cost control and schedule coordination are difficult to balance, resulting in low resource allocation efficiency and unstable project performance. This paper constructs a cost optimization and schedule coordination control model for building engineering based on Building Information Modeling (BIM) technology and Particle Swarm Optimization (PSO) algorithm, realizing visualized, data-driven, and intelligent decision-making for engineering elements. First, a three-dimensional information model of the project is established using a BIM platform, extracting key cost elements and schedule constraints. Second, a bi-objective optimization function is constructed with the objectives of minimizing total project cost and minimizing schedule deviation. Then, an improved PSO algorithm is used, employing dynamic inertia weights and adaptive learning factors to enhance global convergence performance, iteratively solving for the optimal cost-schedule matching scheme. Finally, the results were validated in a large-scale complex project case. The results showed that, compared to the Whale Optimization Algorithm, after the 10th iteration, this method reduced the total project cost by 0.07 billion yuan, shortened the construction period by 16 days, and achieved a cost deviation rate difference of up to 2.5% compared to the WOA model, thus achieving optimal cost-schedule coordination control. This research provides a visualized and intelligent optimization decision-making path for construction project management.
Li Chen (Thu,) studied this question.