Please use this identifier to cite or link to this item:
Title: Long‐Term Forecasting Method in the Supply Chain Based on an Artificial Neural Network with Multi‐Agent Metaheuristic Training
Authors: Fedorov, Eugene
Nechyporenko, Olga
Федоров, Євген Євгенович
Нечипоренко, Ольга Володимирівна
Keywords: long-term forecast;supply chain;metaheuristics;metaheuristics;forecast neural network model
Issue Date: 2021
Publisher: CEUR Workshop Proceedings
Abstract: The problem of increasing the efficiency of long-term forecasting in the supply chain is examined. Neural network forecasting methods that are based on reservoir calculations, which increases the forecast accuracy, are proposed. Methods for identifying parameters of forecast models based on the metaheuristics are proposed for the methods mentioned above. These methods were researched on the basis of the data from the logistics company Ekol Ukraine and are intended for intelligent computer-based supply chain management systems.
ISSN: 1613-0073
Issue: 2864
First Page: 1
End Page: 11
Appears in Collections:Наукові публікації викладачів (ФІТІС)

Files in This Item:
File Description SizeFormat 
paper1.pdf419.9 kBAdobe PDFThumbnail

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.