Dynamic model averaging-based procurement optimization of prefabricated components

With the promotion of construction industrialization, the prefabricated construction market is becoming increasingly competitive. The raw material cost of prefabricated components accounts for a large proportion of the total cost of prefabricated construction project. Effective planning of raw material procurement strategy for prefabricated components can significantly optimize the cost of materials and prefabricated construction project. Considering the impact of material price fluctuation and demand change on the procurement strategy of raw materials for prefabricated components, this study proposes a procurement model of raw materials for prefabricated components, which considers the changing demand and price fluctuation under multiple time series. Firstly, the price of raw materials for prefabricated components is predicted based on dynamic model averaging and dynamic model selection, and then, price is embedded into the procurement and inventory replenishment model. Finally, the raw material procurement strategy with the objective of minimizing procurement cost is generated through genetic algorithm. An application example is presented to demonstrate the capabilities of the procurement strategy model with respect to accuracy of price prediction and optimizing material procurement decisions.