Integrated Planning Approach for Optimizing Tower Crane and Truck Locations in Modular Integrated Construction
Publication: Journal of Construction Engineering and Management
Volume 150, Issue 9
Abstract
Tower crane layout planning (TCLP) is key to ensure the safety and productivity of construction projects. Previous studies on TCLP mainly focused on the typical in situ construction method, however, overlooking modular integrated construction (MiC). This study aims to develop an integrated planning approach for optimizing the locations of tower cranes and trucks for MiC across the entire construction site. This approach consists of four objective components. First, identifying potential locations for cranes and trucks by adopting a gridding method and an intersection examination algorithm. Second, estimating the crane operation duration. Third, optimizing the crane and truck locations by developing an integer linear programming (ILP) model while considering various constraints, such as the demand fulfillment, the crane’s lifting capacity, and the multiple truck parking areas. Lastly, optimizing the distance between cranes to avoid crane blocking on site. The proposed approach is validated via three high-rise residential MiC projects. The results achieve 19.4%–37.9% reductions in cranes’ operation durations, as well as carbon emissions from the original plan. Compared with another existing TCLP method made from limited predefined layout plans, a 29.4% improvement is observed. Moreover, three aspects to extend the application of the approach are discussed: (1) the multiple tower crane layout scenario, (2) the impact of the number of truck points, and (3) the trade-offs between computing effectiveness and performance. The approach realizes the objective of TCLP decision-making for multi-crane multitruck MiC throughout the whole construction site. Construction practitioners can use this approach for decision-making which helps enhance the effectiveness of their tower crane layout designs.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
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© 2024 American Society of Civil Engineers.
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Received: Jun 28, 2023
Accepted: Jan 31, 2024
Published online: Jul 15, 2024
Published in print: Sep 1, 2024
Discussion open until: Dec 15, 2024
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