BIM-based constructability-aware precast building optimization using optimality criteria and combined non-dominated sorting genetic II and great deluge algorithm (NSGA-II-GD)

Abstract

The popularity of precast concrete in construction is rising due to its capacity for improving building efficiency and quality in comparison to cast-in-situ concrete. While researchers have focused on enhancing constructability factors like logistics and sequencing, the need for developing standardization in this area remains evident. This paper describes a framework for studying the relationship between construction cost and standardization by optimizing precast component dimensions and rebar designs. The framework involves using Building Information Modeling techniques to extract semantic information from architectural plans, followed by a gradient-based Optimality Criteria method to optimize the sizing variables of precast components. Finally, a hybrid approach called NSGA-II-GD, which combines the Non-dominated Sorting Genetic Algorithm II and Great Deluge Algorithm, is used to optimize the rebar layout design of each precast component. The Results demonstrate that an optimal point exists between construction cost and standardization, particularly for components subjected to similar stresses. Additionally, the NSGA-II-GD algorithm improves the searching efficiency in terms of convergence, computational time, and searching space.