商贸物流转运中心集货区动态货位分配研究

Dynamic Storage Location Allocation in the Consolidation Area of Commercial and Trade Logistics Transfer Centers

随着我国智能技术与物流设备的深度融合,物流中心逐渐趋于自动化和智能化。本文通过分析商贸物流转运中心货物到达、存储和发出的主要特点,主要研究以AGV自动取货为主导的动态货位分配问题。为保证货物出库流程衔接顺畅省时,考虑集货时间、发车线路、发货站台位置等影响因素,建立以取货时间最短为目标函数的货位分配模型,利用遗传算法求解,得到初始优化结果。引入货位价值概念,调整发货站台后,再求解得到改进优化结果。最后依托山东临沂某商贸物流园区转运中心,以集货区作为主要实验对象。对比分析随机结果、初始优化结果和改进优化结果,改进优化结果可有效节省AGV取货时间,较随机策略约节省10.05%。

With the deep integration of intelligent technology and logistics equipment in China,logistics centers are gradually becoming automated and intelligent.This paper focuses on the dynamic storage location allocation problem dominated by AGV(Automated Guided Vehicle)automatic picking,by analyzing the main characteristics of goods arrival,storage,and dispatch in commercial and trade logistics transfer centers.To ensure a smooth and time-saving outbound process,various factors such as consolidation time,departure routes,and shipping dock locations are considered.A storage location allocation model is established with the objective of minimizing picking time,and solved using a genetic algorithm to obtain initial optimized results.After introducing the concept of storage location value and adjusting the shipping docks,further solutions are obtained as improved optimized results.Finally,relying on a transfer center in a commercial and trade logistics park in Linyi,Shandong,the consolidation area is taken as the main experimental subject.By comparing and analyzing random results,initial optimized results,and improved optimized results,it is found that the improved optimized results can efectively save AGV picking time by approximately 10.05%compared to the random strategy.