An Intelligent Optimization Method of Reinforcing Bar Cutting for Construction Site

To meet the requirements of specifications, intelligent optimization of steel bar blanking can improve resource utilization and promote the intelligent development of sustainable construction. As one of the most important building materials in construction engineering, reinforcing bars (rebar) account for more than 30% of the cost in civil engineering. A significant amount of cutting waste is generated during the construction phase. Excessive cutting waste increases construction costs and generates a considerable amount of CO2 emission. This study aimed to develop an optimization algorithm for steel bar blanking that can be used in the intelligent optimization of steel bar engineering to realize sustainable construction. In the proposed algorithm, the integer linear programming algorithm was applied to solve the problem. It was combined with the statistical method, a greedy strategy was introduced, and a method for determining the dynamic critical threshold was developed to ensure the accuracy of large-scale data calculation. The proposed algorithm was verified through a case study; the results confirmed that the rebar loss rate of the proposed method was reduced by 9.124% compared with that of traditional distributed processing of steel bars, reducing CO2 emissions and saving construction costs. As the scale of a project increases, the calculation quality of the optimization algorithm for steel bar blanking proposed also increases, while maintaining high calculation efficiency. When the results of this study are applied in practice, they can be used as a sustainable foundation for building informatization and intelligent development.