Demand forecast in a supermarket using a hybrid intelligent system

Authors:
Luis Aburto;Richard Weber
Affiliations:
DADS S. A., Santiago, Chile;RCAST, University of Tokyo, Japan
Venue:
Design and application of hybrid intelligent systems
Year:
2003

Citing 7
Cited 2

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Abstract

Demand forecasts play a crucial role in advanced systems for supply chain management. Determining the future demand for a certain product is the basis the respective systems. Several forecasting techniques have been developed, each one with its particular advantages and disadvantages compared to other approaches. This motivates the development of hybrid systems combining different techniques and their respective advantages. In this paper we propose a hybrid forecasting system combining ARIMA models and neural networks. We show improvements in forecasting accuracy and develop a replenishment system based on the respective forecasts for a Chilean supermarket chain.