基于多权重启发优化的物流仓储补货模式优化研究

摘要

In this paper, we proposed a method for the optimization of the logistics warehousing replenishment mode based on multi-weight heuristics, then with product demand frequency, quantity of demand, average sorting volume and average replenishment volume as the basic variables, designed a target function for the optimal efficiency of the mode, solved it using the neural network algorithm to obtain the optimal warehouse replenishment model, and at the end, through an empirical study on a certain distribution center, proved the validity of the method.%传统的物流仓储补货模式使用确定的补货模型确定了补货量、补货点、补货周期等参数，在顾客需求与货物种类变动频繁的情况下补货效率降低，影响了物流生产。提出一种基于多权重启发优化的物流仓储补货模式优化方法，以产品需求频率、需求数量、仓储均拣量、均补货量4个变量为基本模型，设计效率最优的目标函数，将这些参数赋予不同的权重系数，根据客户与货物的实时变化使用神经网络优化法对权重系数优化求解，得到最优的仓储货物补充模型，使用SPSS数据分析软件对某物流配送中心的数据进行测试，证明该优化方法物流补货的效率大大提高，具有很强的实用价值。