Hierarchical supply chain planning using artificial neural networks to anticipate base-level outcomes

DOI10.1007/s00291-004-0170-xzbMath1069.90034OpenAlexW2022550749MaRDI QIDQ1884673

Jens Rohde

Publication date: 5 November 2004

Published in: OR Spectrum (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00291-004-0170-x

zbMATH Keywords

anticipationartificial neural networkhierarchical planningmulti-layerperceptron

Mathematics Subject Classification ID

Production models (90B30) Neural networks for/in biological studies, artificial life and related topics (92B20)

Related Items

Integrated versus hierarchical approach to aggregate production planning and master production scheduling ⋮ Stochastic dynamic lot-sizing problem using bi-level programming base on artificial intelligence techniques ⋮ Applying machine learning for the anticipation of complex nesting solutions in hierarchical production planning