Construction site layout planning (CSLP) is a typical problem in construction site management that urgently needs to be solved. A reasonable construction site layout can improve efficiency and reduce costs and unnecessary loss of time. To solve the CSLP problem, some emerging optimization algorithms and enhanced mathematical models have been developed. The building information model (BIM) provides data support for the implementation of previous research. However, manually extracting and modifying parameters from the BIM for use in optimization algorithms is cumbersome in practical applications, wasting considerable time and human resources. In this paper, we propose a framework of automated prefabricated building CSLP to realize the integration of the BIM and an optimization algorithm, which utilizes the Dynamo visual programming platform to create an information channel between the BIM and the optimization algorithm. A typical and practical case, which is optimized by the genetic algorithm (GA) and particle swarm optimization (PSO), is demonstrated to validate the proposed approach and to show an effective reduction in material transportation cost and unnecessary loss of time.

Effective data interoperability and schedule analysis play a significant role in improving the management of prefabricated buildings. However, there is a lack of efficient strategies and comprehensive approaches for data interoperability and data-based automated schedule analysis. This paper intends to promote prefabricated buildings’ management by solving these two problems via developing an IFC-based framework consisting of three parts. Firstly, this framework proposed a mechanism to establish an IFC-based 4D construction management information model of prefabricated buildings. Furthermore, a non-relational database—graph database—is introduced to twin this model into a task-centered network to realize the interoperation of construction information among different participants. Finally, graph database-based strategies to update data, automatically analyze construction schedules and visualize the 4D construction management information model are described. The proposed framework is validated in a prefabricated engineering case. In this case, an IFC-based and graph database-based 4D construction management information model is established through IFC standard’s extension. The graph database-based analysis of the model automatically recognizes the engineering case’s critical path information, delay analysis information, and schedule network analysis information. It is illustrated that this framework can successfully establish a unified IFC-based information model of prefabricated buildings’ construction management to prompt effective data interoperability. In addition, the application of this IFC-based information model in graph database can automatically analyze the construction schedules to prevent possible delays in advance. In short, the significance of this paper is to innovatively propose an IFC-based and graph data-based information model to solve the difficulties of ineffective data interoperation and unautomated schedule analysis in prefabricated buildings’ construction management. This study can be the digital foundation of further IFC-based digital twin.