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Promet - Traffic&Transportation journal

Accelerating Discoveries in Traffic Science

Accelerating Discoveries in Traffic Science

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Copyright (c) 2024 Francisco Campuzano-Bolarín, Antonio Guillamón Frutos, Ma Del Carmen Ruiz Abellón, Andrej Lisec

Alternative Forecasting Techniques that Reduce the Bullwhip Effect in a Supply Chain: A Simulation Study

Authors:Francisco Campuzano-Bolarín, Antonio Guillamón Frutos, Ma Del Carmen Ruiz Abellón, Andrej Lisec

Abstract

The research of the Bullwhip effect has given rise to many papers, aimed at both analysing its causes and correcting it by means of various management strategies because it has been considered as one of the critical problems in a supply chain. This study is dealing with one of its principal causes, demand forecasting. Using different simulated demand patterns, alternative forecasting methods are proposed, that can reduce the Bullwhip effect in a supply chain in comparison to the traditional forecasting techniques (moving average, simple exponential smoothing, and ARMA processes). Our main findings show that kernel regression is a good alternative in order to improve important features in the supply chain, such as the Bullwhip, NSAmp, and FillRate.

Keywords:Bullwhip effect, supply chain, kernel regression, system dynamics model

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