Forecasting Methods to Reduce Inventory Level in Supply Chain

Tao Cai ,Xiaoshen Li

doi:10.4236/jamp.2022.102023

Abstract

Based on the two-level supply chain composed of suppliers and retailers, we assume that market demand is subject to an ARIMA(1, 1, 1). The supplier uses the minimum mean square error method (MMSE), the simple moving average method (SMA) and the weighted moving average method (WMA) respectively to forecast the market demand. According to the statistical properties of stationary time series, we calculate the mean square error between supplier forecast demand and market demand. Through the simulation, we compare the forecasting effects of the three methods and analyse the influence of the lead-time L and the moving average parameter N on prediction. The results show that the forecasting effect of the MMSE method is the best, of the WMA method is the second, and of the SMA method is the last. The results also show that reducing the lead-time and increasing the moving average parameter improve the prediction accuracy and reduce the supplier inventory level.

Highlights

Inventory problem has been an important problem in supply chain
Based on the two-level supply chain composed of suppliers and retailers, we assume that market demand is subject to an ARIMA(1, 1, 1)
The results show that the forecasting effect of the MMSE method is the best, of the weighted moving average method (WMA) method is the second, and of the simple moving average method (SMA) method is the last

Summary

Introduction

Inventory problem has been an important problem in supply chain. Enterprise in the supply chain has been looking for ways to reduce their inventory levels because savings in inventory levels will eventually translate into cost savings over time. Many pieces of literature have proved that information sharing is an effective method to improve forecasting accuracy and reduce average inventory level. Chain enterprises can only rely on improving forecasting accuracy to reduce their inventory level. Scholars at home and abroad put forward many methods to improve the accuracy of prediction These methods analyze supply chain demand forecasting and inventory control from different aspects. The literature [3] [4] [5] has studied two-level supply chain under ARMA(1, 1), AR(1) and MA(1) demand processes It studied effects of single exponential smoothing method and simple moving average method on mean square error and inventory level, which show that the saving of inventory cost depends on the improvement of forecasting accuracy. This study starts from forecasting methods and forecasting errors to study the influence of three different forecasting strategies on supplier

Objectives

Methods

Results