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    Optimized Planning Approach for Multiple Tower Cranes and Material Supply Points Using Mixed-Integer Programming

    Source: Journal of Construction Engineering and Management:;2020:;Volume ( 146 ):;issue: 003
    Author:
    Yuanshen Ji
    ,
    Fernanda Leite
    DOI: 10.1061/(ASCE)CO.1943-7862.0001781
    Publisher: ASCE
    Abstract: It is common to implement multiple tower cranes on building construction projects. The plan for usage of multiple tower cranes should be optimized for better project performance, such as reduced cost or operation time. Optimization of plans for multiple cranes is complex, especially when considering the supply of transported material (e.g., location, quantity, material type), as well as assigning lift tasks among tower cranes that are in range. This study developed a mathematic formulation that can solve this optimization problem using mixed-integer programming. The formulation introduces several binary variables and restricts the domain of the indices of these variables using an additional set of auxiliary variables. The proposed model contributes to the body of knowledge by showing the feasibility of using mixed-integer-programming techniques to solve the optimization problem of multiple tower cranes and their supply systems. The findings also demonstrate that when a multiple tower crane problem is concerned, optimizing each piece of equipment individually could lead to suboptimal solutions. Specifically, the operation time drops by 6.8% and the operation cost decreases by 3.6% in the two-tower crane case study example. The proposed model can also assist engineers with assessing a large number of alternative plans, which are heavily needed in preconstruction planning, where site layout is preliminary.
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      Optimized Planning Approach for Multiple Tower Cranes and Material Supply Points Using Mixed-Integer Programming

    URI
    https://yetl.yabesh.ir/yetl1/handle/yetl/4265152
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    • Journal of Construction Engineering and Management

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    contributor authorYuanshen Ji
    contributor authorFernanda Leite
    date accessioned2022-01-30T19:21:43Z
    date available2022-01-30T19:21:43Z
    date issued2020
    identifier other%28ASCE%29CO.1943-7862.0001781.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4265152
    description abstractIt is common to implement multiple tower cranes on building construction projects. The plan for usage of multiple tower cranes should be optimized for better project performance, such as reduced cost or operation time. Optimization of plans for multiple cranes is complex, especially when considering the supply of transported material (e.g., location, quantity, material type), as well as assigning lift tasks among tower cranes that are in range. This study developed a mathematic formulation that can solve this optimization problem using mixed-integer programming. The formulation introduces several binary variables and restricts the domain of the indices of these variables using an additional set of auxiliary variables. The proposed model contributes to the body of knowledge by showing the feasibility of using mixed-integer-programming techniques to solve the optimization problem of multiple tower cranes and their supply systems. The findings also demonstrate that when a multiple tower crane problem is concerned, optimizing each piece of equipment individually could lead to suboptimal solutions. Specifically, the operation time drops by 6.8% and the operation cost decreases by 3.6% in the two-tower crane case study example. The proposed model can also assist engineers with assessing a large number of alternative plans, which are heavily needed in preconstruction planning, where site layout is preliminary.
    publisherASCE
    titleOptimized Planning Approach for Multiple Tower Cranes and Material Supply Points Using Mixed-Integer Programming
    typeJournal Paper
    journal volume146
    journal issue3
    journal titleJournal of Construction Engineering and Management
    identifier doi10.1061/(ASCE)CO.1943-7862.0001781
    page04020007
    treeJournal of Construction Engineering and Management:;2020:;Volume ( 146 ):;issue: 003
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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