A Method for Adjusting the Yards Storage Space of Prefabricated Component Based on Inventory Fluctuation Prediction

Abstract

This invention relates a method for adjusting the yards storage space of prefabricated component based on inventory fluctuation prediction belongs to the field of building storage management. This method involves constructing a data set with time-evolving characteristics and spatial constraints; combining a time series prediction model to predict future inventory changes, and using the reinforcement learning algorithm (Q-learning) to dynamically optimize the allocation of the storage yard space. After completing the division of the number of columns in the main area and the buffer area, a static initial column allocation plan is formed. The dynamic optimization adjustment by the reinforcement learning algorithm can achieve efficient management of the storage yard space. Through precise demand prediction and adaptive optimization strategies, this invention can significantly improve the space utilization rate of the storage yard, reduce waste of ineffective space, and effectively lower the adjustment cost. At the same time, the system can respond in real time to fluctuations in production and logistics plans, ensuring that the storage yard layout can be flexibly adjusted in the face of sudden changes, thereby achieving more efficient and stable storage yard management.