在考虑成品库天车能耗的基础上,设计了一种钢材成品库出库算法。该算法采用BP神经网络算法确定候选垛位区域,再通过计算天车运行代价完成目标垛位的选择。仿真验证结果表明,与传统人工指定垛位方法相比,本算法能够有效减少天车运行次数,降低运行能耗,提高成品库运行效率。 Based on the energy consumption of the finished product crane, a steel product storage algorithm is designed. The algorithm uses BP neural network algorithm to determine the candidate stack area, and then chooses the target stack by calculating the crane overhead. Simulation results show that the proposed algorithm can effectively reduce the number of crane runs, reduce energy consumption and improve the operating efficiency of the finished product warehouse, compared with the traditional manually-assigned palletizing method.