Abstract
Abstract Cranes often play a central role in transporting materials on building construction sites and are therefore critical to project cost and schedule. This paper presents a new model to simulate the interactions between mobile cranes and associated work crews onsite. The model considers crane type and position, the sequence of components transported, and the number and size of crews at the demand point. A novel hybrid multi-objective Genetic Algorithm (MOGA) is utilized to identify optimal crane and crew configurations that minimize construction cost and duration. The proposed method is demonstrated on an example problem involving the installation of curtain wall panels for a mid-rise office building. The results indicate that considering crane and crew decisions in parallel reduces installation cost by 19.5% and duration by 1.7% compared to considering these decisions sequentially. Furthermore, the number of crews used and the number of crane stops had the most significant impact on project cost and schedule, respectively.
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