Treffer: Neural Networks in Manufacturing: Possible Impacts on Cutting Stock Problems
Title:
Neural Networks in Manufacturing: Possible Impacts on Cutting Stock Problems
Authors:
Source:
Engineering Management and Systems Engineering Faculty Research & Creative Works
Publisher Information:
Scholars' Mine
Publication Year:
1990
Collection:
Missouri University of Science and Technology (Missouri S&T): Scholars' Mine
Subject Terms:
Computerised Pattern Recognition, Cutting Stock Problems, Feature-Recognition Network, Manufacturing, Manufacturing Data Processing, Neural Nets, Neural Networks, Parallel Processing, Production Control, Simulated Annealing, Stock Control, Operations Research, Systems Engineering and Industrial Engineering
Document Type:
Fachzeitschrift
text
File Description:
application/pdf
Language:
unknown
Relation:
DOI:
10.1109/CIM.1990.128157
Availability:
Rights:
© 1990 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Accession Number:
edsbas.E668D6FF
Database:
BASE
Weitere Informationen
The potential of neural networks is examined, and the effect of parallel processing on the solution of the stock-cutting problem is assessed. The conceptual model proposed integrates a feature-recognition network and a simulated annealing approach. The model uses a neocognitron neural network paradigm to generate data for assessing the degree of match between two irregular patterns. The information generated through the feature recognition network is passed to an energy function, and the optimal configuration of patterns is computed using a simulated annealing algorithm. Basics of the approach are demonstrated with an example.