A simulation-based genetic algorithm schedule optimization method for bridge construction

Off-site construction has become widely acknowledged for its advantages, such as saving time, enabling faster assembly, and being cost-efficient. The sector's rapid growth has driven the demand for more advanced and effective methods of construction scheduling. Construction scheduling is naturally complicated due to the numerous constraints it involves, including those connected to workforce and resource availability. Conventional approaches, like the Critical Path Method (CPM), fail to account for multiple constraints, which limits their effectiveness in practical project scenarios. This research presents a simulation-based Genetic Algorithm (S-GA) approach to develop optimal construction schedules while accounting for constraints in labour and resources. Reducing the total project duration is the objective of proposed method. The proposed S-GA framework enhances the ability to manage scheduling across all construction phases. A real-world case which contains a prefabricated bridge with 6 spans was conducted to assess the method. For comparison, traditional methods and the evolution algorithm (EA) were adopted, and the findings indicated that S-GA not only produced superior construction schedules but also operated with less computational time. Proposed S-GA generated the best construction schedule with shortest project duration within least computational time. As a result, the proposed approach offers an advanced scheduling method that is applicable to real-world construction projects. Project managers could use proposed method to make plans for their construction projects.