Abstract

Optimization of tower crane positioning is essential in precast building construction to ensure that a crane is in the right position to offer the best value for placing precast elements. The first goal is the optimization of transportation distances made by tower cranes, which will address the issues of efficiency and cost. This is done in a way that provides for minimization of the distances that lie between the trailer parking where elements are parked, the tower crane, and the construction installation point. However, current research fails to address the dynamic movement efficiency of trailers, especially when handling multiple trailers and several models of tower cranes, making this scenario an optimization problem that is classified as NP-hard due to the likelihood of causing a combinatorial explosion. This work endeavors to present a new mathematical model that has been applied to the Genetic Algorithm (GA). The ideal demand-generated model is designed to solve the optimal model and position of tower cranes and the prospective positioning of trailers for parking. The feasibility and applicability of the method exploited in the study are also established through a project case study. When adopting the proposed planning model compared to the earlier planning scale, comparisons highlight a small yet significant saving of 6% in time and cost when lifting elements instead of providing them from the trailers by setting up a new on-site stockyard. In addition, a great deal of enhancement is also observed in the final solution aspects, where the developed GA has even reduced the operational time and cost by half a percent each. The results of this research offer best-practice approaches to the position analysis of tower cranes in precast building construction to bring scalability and cost optimization to bear on the construction business.

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