Abstract
Prefabricated construction involves manufacturing components in a factory and then transporting them to a construction site for assembly, yielding resource savings and improved efficiency. However, the large size and weight of prefabricated components, along with strict delivery requirements, introduce logistical challenges, such as increased carbon emissions during transport and site congestion. This study addresses the dual-objective vehicle scheduling problem for prefabricated components. It proposes a dual-objective optimization model for prefabricated component logistics, guided by the Just-In-Time (JIT) strategy. The model comprehensively considers on-site and off-site logistics, accounts for uncertainties, and details the logistics process for each component. Its objectives are to reduce carbon emissions during logistics and enhance customer satisfaction. An improved Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to solve the model, offering enhanced solution diversity and local search capabilities. The model is validated through case studies, with sensitivity analyses conducted to further assess performance. Results indicate that the proposed model provides effective vehicle scheduling solutions that meet optimization objectives. Compared to traditional logistics models, the JIT logistics model demonstrates greater resilience to uncertainty, providing scientifically based decision support for logistics management in prefabricated construction.