The planning effectiveness of construction site layout greatly influences construction efficiency. Many previous studies assumed that all the facilities exist on the construction sites for the whole duration of the projects. Some researchers found the shortcomings and developed models to improve it. But these models also have different limitations, such as ignoring the future impact of the layout decision in early construction phases on the later layout quality, only considering transportation costs when optimize the layouts, etc. To address these issues, this study proposes a building information modeling (BIM)-based model that dynamically optimizes the multi-objective construction site layout. In this model, BIM and construction schedules provide the updated construction project information. This model introduces the construction phase impact on layout. The layout of each construction phase is optimized in order of corresponding phase impact. Considering the sustainable development for construction industry, the noise pollution level is chosen to be the optimization objective together with the total transportation cost. In order to balance the noise pollution level and total transportation cost, the multi-objective particle swarm optimization (MOPSO) is applied to obtain trade-off solutions. A case study is presented to demonstrate the capability of the proposed model. The results indicate that the proposed dynamic construction site layout plan (CSLP) reduces transportation cost by 43.45% and 11.46% compared with the original and static construction site layout. This study breaks the traditional site layout plan order and locates the facilities in order of their phase impact, which can greatly reduce the transportation cost on the site. It also incorporates the noise pollution reduction into CSLP to enhance on-site sustainability.


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    Title :

    Dynamic Multi-objective Construction Site Layout Planning Based on BIM


    Additional title:

    KSCE J Civ Eng


    Contributors:
    Tao, Guowu (author) / Feng, Haibo (author) / Feng, Jingchun (author) / Wang, Tianhao (author)

    Published in:

    Publication date :

    2022-04-01


    Size :

    13 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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