Comparing Statistical and Machine Learning Methods for Time Series Forecasting in Data-Driven Logistics—A Simulation Study

Comparing Statistical and Machine Learning Methods for Time Series Forecasting in Data-Driven Logistics—A Simulation Study

Many planning and decision activities in logistics and supply chain management are based on forecasts of multiple time dependent factors. Therefore, the quality of planning depends on the quality of the forecasts. We compare different state-of-the-art forecasting methods in terms of forecasting perf...

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Bibliographic Details
Main Authors: Lena Schmid, Moritz Roidl, Alice Kirchheim, Markus Pauly
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Entropy
Subjects:
machine learning
time series
forecasting
simulation study
Online Access:https://www.mdpi.com/1099-4300/27/1/25
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