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    Integrating building information modelling and firefly algorithm to optimize tower crane layout

    Access Status
    Fulltext not available
    Authors
    Wang, J.
    Liu, J.
    Shou, W.
    Wang, Xiangyu
    Hou, L.
    Date
    2014
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Wang, J. and Liu, J. and Shou, W. and Wang, X. and Hou, L. 2014. Integrating building information modelling and firefly algorithm to optimize tower crane layout, pp. 321-328: University of Technology Sydney.
    Source Title
    31st International Symposium on Automation and Robotics in Construction and Mining, ISARC 2014 - Proceedings
    ISBN
    9780646597119
    School
    Department of Construction Management
    URI
    http://hdl.handle.net/20.500.11937/18637
    Collection
    • Curtin Research Publications
    Abstract

    Tower crane layout design and planning within construction site is a common construction technical issue and regarded as a complex combinatorial problem. To transport heavy materials, such as rebar, formwork, scaffolding, equipment and steel, tower cranes are needed and should be well located to reduce construction cost and improve safety management. Currently, practitioners in the industry are over-reliance on individual experience and subjective judgment during decision-making process. The purpose of this paper wants to develop a well-defined approach, which integrating Building Information Modelling (BIM) and firefly algorithm to come up with an optimal tower crane layout for construction projects. Firstly, BIM technology is utilized to automatically generate the quantity of materials which need to be transported. Then firefly algorithms are used to determine the locations of tower cranes, supply points and demand points according to transportation requirement, time and cost. Thirdly, the optimal tower crane layout scheme will be visualized by 4-Dimension (4D) BIM to verify its constructability and safety based on computer simulation and individual experience. Finally, a practical case is selected to evaluate the developed approach. In addition, some lessons learned and issues are highlighted that help direct future research and implementation. The optimization results of the example are very promising and it demonstrates the application value of the approach.

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