New Optimization Method Dramatically Improves Prefabricated Construction Site Efficiency & Safety
Sanya, China – A novel optimization method promises to revolutionize the planning of prefabricated construction sites, considerably reducing risks and costs associated with tower crane logistics and workspace congestion. Published in Front. Eng. Manag. (2025, 12(3): 487-509), the research details a Hybrid Multi-objective Decision Making (HMSIDBO)-based approach to Prefabricated Construction Crane Scheduling and Layout Planning (PCCSLP).
The escalating adoption of prefabricated construction demands smarter site management to overcome challenges like limited space, complex crane movements, and potential safety hazards from falling components. This new method addresses these issues head-on, offering a data-driven framework for optimizing site layout from initial data collection through multi-objective optimization. The research demonstrates improvements ranging from 18% to 75% across key metrics, impacting project managers, construction workers, and ultimately, the cost and timeline of prefabricated building projects.
The HMSIDBO-PCCSLP model tackles three core objectives: minimizing horizontal transportation time for tower cranes, shortening the horizontal path length for lifting prefabricated components, and reducing overlapping work areas between multiple cranes.It operates within seven constraints, encompassing four boundary limitations and three addressing potential overlaps. A case study conducted on prefabricated residential projects in Sanya, China, validated the method’s practicality and effectiveness.
Results show the HMSIDBO optimization scheme outperforms existing approaches.Compared to the original layouts, it reduces average horizontal transportation time by 18.3%, shrinks hazardous areas affected by falling components by 23.4%, and decreases overlapping work areas by 74.3%. Furthermore, HMSIDBO proved computationally faster and more accurate than Genetic Algorithms (GA), and exhibited superior iterative speed and global exploration capabilities when compared to the Dung Beetle Optimizer (DBO), Particle Swarm Optimization (PSO), and Whale Optimization Algorithm (WOA).
the full study is available at: https://doi.org/10.1007/s42524-024-4004-z. This research lays the groundwork for wider implementation of bright construction site layouts and provides a scientific basis for safer, more efficient prefabricated construction management.
