With the increasing prevalence of modular integrated construction (MiC) projects, effective tower crane layout planning has become crucial to balance multiple goals, including efficiency and safety. Studies typically focus on single-objective optimization, primarily minimizing total traveling time or cost in conventional construction sites. The larger and heavier components used in MiC necessitate cranes with higher lifting capacity, which complicates planning and raises concerns about lifting safety. This study presents a two-stage optimization design framework for the single-tower crane layout in MiC. First, a multiobjective optimization model was proposed, incorporating considerations of traveling time, visibility, and lifting moment. The mathematical formulation for traveling time was modified to account for module rotation time and the distinct movement features of tower cranes. Second, heuristic algorithms, including the nondominated sorting genetic algorithm III and multiobjective particle swarm optimization, were employed to solve the proposed multiobjective optimization problem. The final optimal layout was determined using the technique for order of preference by similarity to ideal solution method based on varying weights for the model’s objectives. The proposed approach was validated through a case study of a MiC project in Hong Kong. Experimental results demonstrate a 26% increase in hoisting efficiency, a 9.3% improvement in operator visibility, and a 23.8% reduction in total lifting moment compared to the original layout. Additionally, optimizing the initial orientation of the modules leads to a 12.6% improvement in traveling time. To further support decision-making, a user interface system was developed, enabling planners to make informed choices during the planning process. This study provides a structured and practical approach for optimizing tower crane layouts in modular construction projects, integrating efficiency and safety considerations. By offering practitioners tools to achieve customized layout solutions during the preconstruction stage, this framework significantly enhances the planning process for MiC projects.
Li et al. (Thu,) studied this question.