Neural networks and production planning

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

Research output: Book/ReportBookScientific


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


Cite this

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.