Neural networks and production planning

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

Research output: Book/ReportBookScientific

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
Publication statusPublished - 1991
Externally publishedYes

Publication series

NameMemorandum COSOR

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Zwietering, P. J., Kraaij van, M. J. A. L., Aarts, E. H. L., & Wessels, J. (1991). Neural networks and production planning. (Memorandum COSOR). Technische Universiteit Eindhoven.