ARTIFICIAL NEURAL NETWORKS AS SUPPORT FOR SCHEDULING IN FOOD INDUSTRY
Matteo Brandolini, Alessandro Di Conza, Sergio De Michelis, Valentina Barcucci, Guido Boero
Liophant Simulation Club
Via Molinero 1, 17100 Savona, Italy
info@liophant.org
www.liophant.org
ABSTRACT
This study examines the implementation and testing of a scheduler in a pasta production facility. It concentrates on experimental performance analysis of the planning through traditional and innovative metrics based on the application of Neural Networks, in particular BPN (back propagation network) and their training using modelling and simulation (M&S) techniques.
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