Neural networks and production planning

P.J. Zwietering, M.J.A.L. Kraaij, van, E.H.L. Aarts, J. Wessels

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Abstract

Because of the combination of classification, association, adaptation, and pattern recognition capabilities, neural networks are shown to be suitable for solving problems in production planning with uncertain and non-stationary demand. We demonstrate that a properly designed and trained multi-layered perceptron outperforms traditional algorithms for the rolling horizon version of the dynamic lotsizing problem. Formal arguments are supported by numerical experiments. Keywords: Lotsizing, Multi-Layered Perceptrons, Neural Networks, Pattern Recognition, Production Planning, Uncertainty.
Original languageEnglish
Place of PublicationEindhoven
PublisherTechnische Universiteit Eindhoven
Number of pages16
Publication statusPublished - 1991

Publication series

NameMemorandum COSOR
Volume9115
ISSN (Print)0926-4493

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