A non-centralized adaptive method for dynamic planning of construction components storage areas. (January 2019) - Li, Kaiman; Luo, Hanbin; Skibniewski, Mirosław J.
Highlights: A novel method was proposed for allocating incoming components in limited site space. This study developed a model for the storage area planning and applied it. A method was firstly presented to identify unoccupied locations in real time. Intelligently acquired variables were considered in GA. Abstract: Rehandling of construction components, such as pipes, structural steel elements, and curtain walls, may increase the handling cost and reduce the construction efficiency, which is a critical issue for storage area plans of a project. Moreover, on some construction sites where space is limited, there are not adequate storage areas for centralized stacking of components and frequent changes in spatial state. Existing studies have investigated site layout planning for temporary facilities including arranging a storage area for the same type of material, which still have limitations in solving the above problems. This study proposes a novel and flexible arrangement method for incoming components in limited site space. This method is non-centralized and adaptive to the dynamic change of the actual component requirements based on construction activities and the real-time storage area availability. Therefore, a construction components storage areas planning (CCSAP) model is developed for dynamic allocation of construction components storage areas. Building information modeling (BIM) can be used to generate the material requirements planning before construction according to the actual construction activities. Real-time spatial recognition is a critical step for dynamic allocation of construction components storage areas because no such research has been done. This paper firstly presents an imaging technology with a low-rank matrix to identify on-site unoccupied locations automatically in real time. In addition, genetic algorithms (GA) consider two types of decision variables: actual components supply and real-time space availability. Finally, a dynamic visualization platform is built for planning construction components storage areas. An implementation example is demonstrated to validate principles and this model and shows a 21.9% reduction in the handling cost and a 19.4% increase in the construction efficiency compared with conventional methods.