Dynamic Multiobjective Optimization Model for Construction Site Layout in Prefabricated Projects

Construction sites in prefabricated construction projects face significant challenges in construction site layout planning (CSLP) because of the simultaneous operation of multiple lifting equipment and the handling of large, heavy components. With the complex and dynamic nature of these construction sites, existing models have yet to fully address the issue of competition for optimal facility locations, even when facilities do not coexist on-site at the same time. This study proposes a dynamic multiobjective optimization model for the CSLP problem in prefabricated construction projects, incorporating the actual existence time of facilities to balance two key objectives: minimizing the hoisting time of the tower crane and reducing potential hazards posed by facilities. The Pareto-optimal solutions are obtained using the oMOAHA algorithm, which enhances the exploration process during initialization and mitigates the risk of local optimization. A prefabricated steel structure project is used to evaluate the effectiveness of the proposed model in two scenarios: a fixed construction schedule and a modified construction schedule during the construction process. The results demonstrate that the proposed model outperforms previous approaches in terms of both objective function value and the number of solutions found. This study provides an effective solution for optimizing available space on construction sites, enabling new facilities to fully reuse locations vacated by previous facilities—an issue not adequately addressed by static and phased approaches in multiobjective trade-offs. Furthermore, the approach presented in this study offers a viable solution for adapting to construction schedule changes during the project, a challenge that has not been effectively addressed in previous research. As a result, this study advances optimization methods for CSLP problems in construction management and provides a solid foundation for future research in more complex construction projects.