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Computer Science > Neural and Evolutionary Computing

arXiv:0906.1900 (cs)
[Submitted on 10 Jun 2009]

Title:How deals with discrete data for the reduction of simulation models using neural network

Authors:Philippe Thomas (CRAN), André Thomas (CRAN)
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Abstract: Simulation is useful for the evaluation of a Master Production/distribution Schedule (MPS). Also, the goal of this paper is the study of the design of a simulation model by reducing its complexity. According to theory of constraints, we want to build reduced models composed exclusively by bottlenecks and a neural network. Particularly a multilayer perceptron, is used. The structure of the network is determined by using a pruning procedure. This work focuses on the impact of discrete data on the results and compares different approaches to deal with these data. This approach is applied to sawmill internal supply chain
Subjects: Neural and Evolutionary Computing (cs.NE)
Cite as: arXiv:0906.1900 [cs.NE]
  (or arXiv:0906.1900v1 [cs.NE] for this version)
  https://doi.org/10.48550/arXiv.0906.1900
Journal reference: 13th IFAC Symp. On Information Control Problems in Manufacturing INCOM'09, Moscou : Russie (2009)

Submission history

From: Philippe Thomas [view email] [via CCSD proxy]
[v1] Wed, 10 Jun 2009 09:56:29 UTC (137 KB)
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