关键词: k-means算法, 储位优化, 多层穿梭车系统, 开环排队网络, 输送机缓存长度

Abstract: At present, the multi-shuttle system has problems such as the unsuitable conveyor's buffer length, which leads to problems such as outbound block or picking idle, affecting the overall efficiency of the system. To improve the operation efficiency of the multi-shuttle system and reduce the input cost of the conveying equipment, based on in-depth analysis of the multi-shuttle system outbound operation process, the conveyor buffer input and output balance model is established; In the case of normal operation of the picking operation, the optimal conditions and critical conditions of the buffer length are proposed. The open queuing network modeling method is used to analyze the outbound operation process of the case, and the average outbound-time model of the case is established. According to the relationship between the flow distribution of the case outbound operation and the manual picking efficiency, the optimization of the buffer length model of the conveyor is established; In order to shorten the average outbound time of the case, the k-means clustering algorithm and the storage arrangement rule are used to optimize the storage position, further reducing the conveyor buffer length. The simulation results show that the optimized item allocation is more reasonable than the random allocation, and the replenishment buffer length is reduced by about 12%. On the one hand, this study can guide the designer to design the conveyor buffer length, on the other hand, it can improve the overall operating efficiency of the system and reduce the operating cost.

Key words: conveyor buffer length, k-means algorithm, multi-shuttle system, open queuing networks, storage assignment optimization