Demand Forecasting Tool For Inventory Control Smart Systems

Intermittent demand forecasting for inventory control: A multi-series approach

This paper is concerned with identifying an effective method for forecasting the lead time demand of slow-moving inventories. Particular emphasis is placed on prediction distributions instead of point predictions alone. It is also placed on methods which work with small samples as well as large samples in recognition of the fact that the typical range of items has a mix of vintages due to diffe...

Guaranteed cost control for multi-inventory systems with uncertain demand

In this paper we consider the problem of controlling a multi–inventory system in the presence of uncertain demand. The demand is unknown but bounded in an assigned compact set. The control input is assumed to be also constrained in a compact set. We consider an integral cost function of the buffer level and we face the problem of minimizing the worst case cost. We show that the optimal cost of ...

Forecasting for Inventory Control with Exponential Smoothing

Integrated Forecasting and Inventory Control for Seasonal Demand: A Comparison with the Holt-Winters Approach

We present a data-driven forecasting technique with integrated inventory control for seasonal data and compare it to the traditional Holt-Winters algorithm. Results indicate that the datadriven approach achieves a 2-5% improvement in the average regret.

A Meta Forecasting Methodology for Large Scale Inventory Systems with Intermittent Demand

This paper presents a meta-forecasting approach for recommending the most appropriate forecasting technique for an intermittent demand series based on a multinomial logistic regression classifier. The meta-forecaster is based on a mapping between a demand attribute space and the best forecasting technique. The demand attribute space is based on the estimates from the demand series of the follow...