基于智能优化的钢筋自动一维下料及分拣技术.

In order to improve the utilization rate of materials, a rebar cutting optimum model used integer programming and gradient boosting decision tree was established considering the influence of processing equipment on one-dimensional rebar products. On that basis, a product sorting optimum model used greedy algorithm was established combined with the intelligent sorting device independently developed by research group, it could promote rebar cutting optimum application in production and improve production efficiency. A case study shows that the presented cutting optimum method has more advantages than the traditional optimal methods in convergence performance, searching effectiveness and solution stability, and the utilization rate of materials has been effectively improved. The sorting optimization reduces the work intensity of field personnel, and greatly improve sorting efficiency. The presented method can guarantee the cost, quality, and efficiency of process, and provides a new way for one-dimensional rebar production in construction. [ABSTRACT FROM AUTHOR]